default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDBriefings in Bioinformatics, Volume 25
Volume 25, Number 1, November 2023
- Junjie Zhu, Zhengxin Li, Haowei Tong, Zhouyu Lu, Ningjie Zhang, Ting Wei, Hai-Feng Chen
:
Phanto-IDP: compact model for precise intrinsically disordered protein backbone generation and enhanced sampling. - Dong Liu, Biao Zhang, Jun Liu, Hui Li, Le Song, Guijun Zhang:
Assessing protein model quality based on deep graph coupled networks using protein language model. - Milos Musil, Andrej Jezik, Jana Horackova, Simeon Borko, Petr Kabourek, Jirí Damborský, David Bednar:
FireProt 2.0: web-based platform for the fully automated design of thermostable proteins. - Francis Yew Fu Tieng, Muhammad Redha Abdullah Zawawi, Nur Alyaa Afifah Md Shahri, Zeti-Azura Mohamed-Hussein, Learn-Han Lee, Nurul-Syakima Ab Mutalib:
A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools. - Jiawei Zhang, Wang Ma, Hui Yao:
Accurate TCR-pMHC interaction prediction using a BERT-based transfer learning method. - Miles McGibbon, Steven R. Shave, Jie Dong, Yumiao Gao, Douglas R. Houston, Jiancong Xie, Yuedong Yang, Philippe Schwaller, Vincent Blay:
From intuition to AI: evolution of small molecule representations in drug discovery. - Nhat Truong Pham, Le Thi Phan, Jimin Seo, Yeonwoo Kim, Minkyung Song, Sukchan Lee, Young-Jun Jeon, Balachandran Manavalan:
Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach. - Wenxuan Xing, Jie Zhang, Chen Li, Yujia Huo, Gaifang Dong:
iAMP-Attenpred: a novel antimicrobial peptide predictor based on BERT feature extraction method and CNN-BiLSTM-Attention combination model. - Qingyang Yin, Liang Chen:
CellTICS: an explainable neural network for cell-type identification and interpretation based on single-cell RNA-seq data. - Zikun Yang, Basilio Cieza, Dolly Reyes-Dumeyer, Rosa Montesinos, Marcio Soto-Añari, Nilton Custodio, Giuseppe Tosto:
A benchmark study on current GWAS models in admixed populations. - Yajie Meng, Yi Wang, Junlin Xu, Changcheng Lu, Xianfang Tang, Tao Peng, Ben-gong Zhang, Geng Tian, Jialiang Yang:
Drug repositioning based on weighted local information augmented graph neural network. - Elena Lucy Carter, Chrystala Constantinidou, Mohammad Tauqeer Alam:
Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations. - Ping Fu, Yifan Wu, Zhiyuan Zhang, Ye Qiu, Yirong Wang, Yousong Peng:
VIGA: a one-stop tool for eukaryotic virus identification and genome assembly from next-generation-sequencing data. - Yu Mei Wang, Yuzhi Sun, Beiying Wang, Zhiping Wu, Xiao-Ying He, Yuansong Zhao:
Transfer learning for clustering single-cell RNA-seq data crossing-species and batch, case on uterine fibroids. - Peilong Li, Junfeng Wei, Ying Zhu:
CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation. - Correction to: Breaking the barriers of data scarcity in drug-target affinity prediction.
- Daniel Toro-Domínguez, Jordi Martorell-Marugan, Manuel Martínez-Bueno, Raúl López-Domínguez, Elena Carnero-Montoro, Guillermo Barturen, Daniel Goldman, Michelle Petri, Pedro Carmona-Saez, Marta E. Alarcón-Riquelme:
Response to the letter 'testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis'. - Sang-Ho Yoon, Jin-Wu Nam:
Clustering malignant cell states using universally variable genes. - Jiaxian Yan, Zhaofeng Ye, Ziyi Yang, Chengqiang Lu, Shengyu Zhang, Qi Liu, Jiezhong Qiu:
Multi-task bioassay pre-training for protein-ligand binding affinity prediction. - Pavel Akhtyamov, Layal Shaheen, Mikhail Raevskiy, Alexey Stupnikov, Yulia A. Medvedeva:
scATAC-seq preprocessing and imputation evaluation system for visualization, clustering and digital footprinting. - Jie Dong, Zheng Wu, Huanle Xu, Defang Ouyang:
FormulationAI: a novel web-based platform for drug formulation design driven by artificial intelligence. - So-Ra Han, Mingyu Park, Sai Kosaraju, Jeungmin Lee, Hyun Lee, Jun Hyuck Lee, Tae-Jin Oh, Mingon Kang:
Evidential deep learning for trustworthy prediction of enzyme commission number. - Jorge Beltrán, Lisandra Herrera Belén, Jorge G. Farias, Mauricio Zamorano, Nicolás Lefin, Javiera Miranda, Fernanda Parraguez Contreras:
VirusHound-I: prediction of viral proteins involved in the evasion of host adaptive immune response using the random forest algorithm and generative adversarial network for data augmentation. - Cuiling Wu, Yiyi Zhang, Zhiwen Ying, Ling Li, Jun Wang, Hui Yu, Mengchen Zhang, Xianzhong Feng, Xinghua Wei, Xiaogang Xu:
A transformer-based genomic prediction method fused with knowledge-guided module. - Min Zou, Honghao Li, Dongqing Su, Yuqiang Xiong, Haodong Wei, Shiyuan Wang, Hongmei Sun, Tao Wang, Qilemuge Xi, Yongchun Zuo, Lei Yang:
Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes. - Hao Qian, Wenjing Huang, Shikui Tu, Lei Xu:
KGDiff: towards explainable target-aware molecule generation with knowledge guidance. - Jan Stourac, Simeon Borko, Rayyan T. Khan, Petra Pokorna, Adam Dobias, Joan Planas-Iglesias, Stanislav Mazurenko, Gaspar R. P. Pinto, Veronika Szotkowska, Jaroslav Sterba, Ondrej Slaby, Jirí Damborský, David Bednar:
PredictONCO: a web tool supporting decision-making in precision oncology by extending the bioinformatics predictions with advanced computing and machine learning. - Lei Chen, Yuwei Chen:
RMTLysPTM: recognizing multiple types of lysine PTM sites by deep analysis on sequences. - Zhen-Ning Yin, Fei-Liao Lai, Feng Gao:
Unveiling human origins of replication using deep learning: accurate prediction and comprehensive analysis. - Qiyiwen Zhang, Changgee Chang, Qi Long:
Robust knowledge-guided biclustering for multi-omics data. - Ruofan Ding, Xudong Zou, Yangmei Qin, Lihai Gong, Hui Chen, Xuelian Ma, Shouhong Guang, Chen Yu, Gao Wang, Lei Li:
xQTLbiolinks: a comprehensive and scalable tool for integrative analysis of molecular QTLs. - Qisheng Pan, Stephanie Portelli, Thanh-Binh Nguyen, David B. Ascher:
Characterization on the oncogenic effect of the missense mutations of p53 via machine learning. - Stavros Makrodimitris, Bram Pronk, Tamim Abdelaal, Marcel J. T. Reinders:
An in-depth comparison of linear and non-linear joint embedding methods for bulk and single-cell multi-omics. - Shuheng Pan, Xinyi Jiang, Kai Zhang:
WSGMB: weight signed graph neural network for microbial biomarker identification. - Qilin Wang, Junyou Zhang, Zhaoshuo Liu, Yingying Duan, Chunyan Li:
Integrative approaches based on genomic techniques in the functional studies on enhancers. - Fanding Xu, Zhiwei Yang, Lizhuo Wang, Deyu Meng, Jiangang Long:
MESPool: Molecular Edge Shrinkage Pooling for hierarchical molecular representation learning and property prediction. - Juntao Li, Hongmei Zhang, Bingyu Mu, Hongliang Zuo, Kanglei Zhou:
Identifying phenotype-associated subpopulations through LP_SGL. - Jiahao Zheng, Yuedong Yang, Zhiming Dai:
Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering. - Zhen Wang, Zheng Feng, Yanjun Li, Bowen Li, Yongrui Wang, Chulin Sha, Min He, Xiaolin Li:
BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation. - Benzhe Su, Weiwei Wang, Xiaohui Lin, Shenglan Liu, Xin Huang:
Identifying the potential miRNA biomarkers based on multi-view networks and reinforcement learning for diseases. - Kevin Tippenhauer, Marwin Philips, Carlo R. Largiadèr, Murat Sariyar:
Using the PharmCAT tool for Pharmacogenetic clinical decision support.
Volume 25, Number 2, January 2024
- Rajesh Kumar Pathak, Jun-Mo Kim:
Veterinary systems biology for bridging the phenotype-genotype gap via computational modeling for disease epidemiology and animal welfare. - Fengjuan Huang, Xinjie Fan, Ying Wang, Yu Zou, Jiangfang Lian, Chuang Wang, Feng Ding, Yunxiang Sun:
Computational insights into the cross-talk between medin and Aβ: implications for age-related vascular risk factors in Alzheimer's disease. - Sheng-Yong Xu, Shanshan Cai, Zhi-Qiang Han:
Evaluating the efficacy of MEANGS for mitochondrial genome assembly of cartilaginous and ray-finned fish species. - Minghao Fang, Jingwen Fang, Songwen Luo, Ke Liu, Qiaoni Yu, Jiaxuan Yang, Youyang Zhou, Zongkai Li, Ruoming Sun, Chuang Guo, Kun Qu:
eccDNA-pipe: an integrated pipeline for identification, analysis and visualization of extrachromosomal circular DNA from high-throughput sequencing data. - Yi-Heng Zhu, Zi Liu, Yan Liu, Zhiwei Ji, Dong-Jun Yu:
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein-DNA binding site prediction. - Hangjia Zhao, Michael Baudis:
labelSeg: segment annotation for tumor copy number alteration profiles. - Simone Maestri, Mattia Furlan, Logan Mulroney, Lucia Coscujuela Tarrero, Camilla Ugolini, Fabio Dalla Pozza, Tommaso Leonardi, Ewan Birney, Francesco Nicassio, Mattia Pelizzola:
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing. - Ariadna Llop-Peiró, Gerard Pujadas, Santiago Garcia-Vallvé:
Challenges in distinguishing functional proteins from polyproteins in databases: implications for drug discovery. - Yuyao Zhai, Liang Chen, Minghua Deng:
scEVOLVE: cell-type incremental annotation without forgetting for single-cell RNA-seq data. - Sowmya Ramaswamy Krishnan, Arijit Roy, M. Michael Gromiha:
Reliable method for predicting the binding affinity of RNA-small molecule interactions using machine learning. - Wang Xu, Houfang Zhang, Wenhan Guo, Lijun Jiang, Yunjie Zhao, Yunhui Peng:
Deciphering principles of nucleosome interactions and impact of cancer-associated mutations from comprehensive interaction network analysis. - Xinyu Guo, Liang Chen:
From G1 to M: a comparative study of methods for identifying cell cycle phases. - Musu Yuan, Hui Wan, Zihao Wang, Qirui Guo, Minghua Deng:
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data. - Mengting Niu, Chunyu Wang, Yaojia Chen, Quan Zou, Lei Xu:
Identification, characterization and expression analysis of circRNA encoded by SARS-CoV-1 and SARS-CoV-2. - Qiuchen Meng, Lei Wei, Kun Ma, Ming Shi, Xinyi Lin, Joshua W. K. Ho, Yinqing Li, Xuegong Zhang:
scDecouple: decoupling cellular response from infected proportion bias in scCRISPR-seq. - Songqi Zhou, Yang Li, Wenyuan Wu, Li Li:
scMMT: a multi-use deep learning approach for cell annotation, protein prediction and embedding in single-cell RNA-seq data. - Mona Nourbakhsh, Kristine Degn, Astrid Saksager, Matteo Tiberti, Elena Papaleo:
Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks. - Jiaxuan Liu, Yonggang Lu, Li Zhu:
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction. - Yury A Barbitoff, Mikhail O. Ushakov, Tatyana E. Lazareva, Yulia A Nasykhova, Andrey S. Glotov, Alexander V. Predeus:
Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges. - Yaofeng Hu, Kai Xiao, Hengyu Yang, Xiaoping Liu, Chuanchao Zhang, Qianqian Shi:
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics. - Lu-Xiang Guo, Lei Wang, Zhu-Hong You, Chang-Qing Yu, Meng-Lei Hu, Bo-Wei Zhao, Yang Li:
Likelihood-based feature representation learning combined with neighborhood information for predicting circRNA-miRNA associations. - Junxiang Zeng, Xiupan Gao, Limei Gao, Youyou Yu, Lisong Shen, Xiujun Pan:
Recognition of rare antinuclear antibody patterns based on a novel attention-based enhancement framework. - Merve Vural-Ozdeniz, Kubra Calisir, Rana Acar, Aysenur Yavuz, Mustafa M. Ozgur, Ertugrul Dalgic, Ozlen Konu:
CAP-RNAseq: an integrated pipeline for functional annotation and prioritization of co-expression clusters. - Lijuan Wang, Ying Lu, Doudou Li, Yajing Zhou, Lili Yu, Ines Mesa Eguiagaray, Harry Campbell, Xue Li, Evropi Theodoratou:
The landscape of the methodology in drug repurposing using human genomic data: a systematic review. - Min Sun, Jing Chen, Chang Zhao, Lihua Zhang, Maili Liu, Yukui Zhang, Qun Zhao, Zhou Gong:
Enhancing protein dynamics analysis with hydrophilic polyethylene glycol cross-linkers. - Jing Meng, Jingze Liu, Wenkai Song, Honglei Li, Jiangyuan Wang, Le Zhang, Yousong Peng, Aiping Wu, Taijiao Jiang:
PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network. - Gulam Sarwar Chuwdhury, Yunshan Guo, Chi-Leung Chiang, Ka-On Lam, Ngar-Woon Kam, Zhonghua Liu, Wei Dai:
ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction. - Yue Guo, Haitao Hu, Wenbo Chen, Hao Yin, Jian Wu, Chang-Yu Hsieh, Qiaojun He, Ji Cao:
SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction. - Giovanni Visonà, Emmanuelle Bouzigon, Florence Demenais, Gabriele Beate Schweikert:
Network propagation for GWAS analysis: a practical guide to leveraging molecular networks for disease gene discovery. - Céline Brouard, Raphaël Mourad, Nathalie Vialaneix:
Should we really use graph neural networks for transcriptomic prediction? - Chengcheng Zhang, Tianyi Zang, Tianyi Zhao:
KGE-UNIT: toward the unification of molecular interactions prediction based on knowledge graph and multi-task learning on drug discovery. - Jici Jiang, Hongdi Pei, Jiayu Li, Mingxin Li, Quan Zou, Zhibin Lv:
FEOpti-ACVP: identification of novel anti-coronavirus peptide sequences based on feature engineering and optimization. - Zhen-Hao Guo, Yan-Bin Wang, Siguo Wang, Qinhu Zhang, De-Shuang Huang:
scCorrector: a robust method for integrating multi-study single-cell data. - Youngjune Park, Nils P. Muttray, Anne-Christin Hauschild:
Species-agnostic transfer learning for cross-species transcriptomics data integration without gene orthology. - Olivier Cinquin:
ChIP-GPT: a managed large language model for robust data extraction from biomedical database records. - Yibo Zhang, Wenyu Liu, Junbo Duan:
On the core segmentation algorithms of copy number variation detection tools. - Yan Miao, Zhenyuan Sun, Chenjing Ma, Chen Lin, Guohua Wang, Chunxue Yang:
VirGrapher: a graph-based viral identifier for long sequences from metagenomes. - Qingyue Wei, Md Tauhidul Islam, Yuyin Zhou, Lei Xing:
Self-supervised deep learning of gene-gene interactions for improved gene expression recovery. - Aleksandra E. Badaczewska-Dawid, Karol Wroblewski, Mateusz Kurcinski, Sebastian Kmiecik:
Structure prediction of linear and cyclic peptides using CABS-flex. - Lingyan Zheng, Shuiyang Shi, Xiuna Sun, Mingkun Lu, Yang Liao, Sisi Zhu, Hongning Zhang, Ziqi Pan, Pan Fang, Zhenyu Zeng, Honglin Li, Zhaorong Li, Weiwei Xue, Feng Zhu:
MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics. - Seokjin Han, Ji Eun Lee, Seolhee Kang, Minyoung So, Hee Jin, Jang Ho Lee, Sunghyeob Baek, Hyungjin Jun, Tae Yong Kim, Yun-Sil Lee:
Standigm ASK™: knowledge graph and artificial intelligence platform applied to target discovery in idiopathic pulmonary fibrosis. - Jin Zhang, Zikang Ma, Yan Yang, Lei Guo, Lei Du:
Modeling genotype-protein interaction and correlation for Alzheimer's disease: a multi-omics imaging genetics study. - Shuang Gu, Chaoliang Wen, Zhen Xiao, Qiang Huang, Zheyi Jiang, Honghong Liu, Jia Gao, Junying Li, Congjiao Sun, Ning Yang:
MyoV: a deep learning-based tool for the automated quantification of muscle fibers. - Fabio N. de Mello, Ana C. Tahira, Maria Gabriela Berzoti-Coelho, Sergio Verjovski-Almeida:
The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping. - Yue Zang, Xia Ran, Jie Yuan, Hao Wu, Youya Wang, He Li, Huajing Teng, Zhongsheng Sun:
Genomic hallmarks and therapeutic targets of ribosome biogenesis in cancer. - Zeyu Luo, Rui Wang, Yawen Sun, Junhao Liu, Herman Z. Q. Chen, Yu-Juan Zhang:
Interpretable feature extraction and dimensionality reduction in ESM2 for protein localization prediction. - Shi Zhang, Rui Zhang, Kai Yuan, Lu Yang, Chang Liu, Yuting Liu, Xumin Ni, Shuhua Xu:
Reconstructing complex admixture history using a hierarchical model. - Shuo Li, Yan Liu, Long-Chen Shen, He Yan, Jiangning Song, Dong-Jun Yu:
GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference. - Albert Katchborian-Neto, Matheus F. Alves, Paula C. P. Bueno, Karen de Jesus Nicácio, Miller S. Ferreira, Tiago B. Oliveira, Henrique Barbosa, Michael Murgu, Ana C. C. de Paula Ladvocat, Danielle F. Dias, Marisi G. Soares, João Henrique Ghilardi Lago, Daniela A Chagas-Paula:
Integrative open workflow for confident annotation and molecular networking of metabolomics MSE/DIA data. - Xiaodi Yang, Stefan Wuchty, Zeyin Liang, Li Ji, Bingjie Wang, Jialin Zhu, Ziding Zhang, Yujun Dong:
Multi-modal features-based human-herpesvirus protein-protein interaction prediction by using LightGBM. - Kandarp Joshi, Dan O. Wang:
epidecodeR: a functional exploration tool for epigenetic and epitranscriptomic regulation. - Yantong Cai, Jia Lv, Rui Li, Xiaowen Huang, Shi Wang, Zhenmin Bao, Qifan Zeng:
Deqformer: high-definition and scalable deep learning probe design method. - Jingxuan Qiu, Wanchun Nie, Hao Ding, Jia Dai, Yiwen Wei, Dezhi Li, Yuxi Zhang, Junting Xie, Xinxin Tian, Nannan Wu, Tianyi Qiu:
PB-LKS: a python package for predicting phage-bacteria interaction through local K-mer strategy. - Wenyuan Ma, Hui Wu, Yiran Chen, Hongxia Xu, Junjie Jiang, Bang Du, Mingyu Wan, Xiaolu Ma, Xiaoyu Chen, Lili Lin, Xinhui Su, Xuanwen Bao, Yifei Shen, Nong Xu, Jian Ruan, Haiping Jiang, Yongfeng Ding:
New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges. - Tingpeng Yang, Tianze Ling, Boyan Sun, Zhendong Liang, Fan Xu, Xiansong Huang, Linhai Xie, Yonghong He, Leyuan Li, Fuchu He, Yu Wang, Cheng Chang:
Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.
Volume 25, Number 3, 2024
- Hui Wang, Dong Liu, Kailong Zhao, Yajun Wang, Guijun Zhang:
SPDesign: protein sequence designer based on structural sequence profile using ultrafast shape recognition. - Pengyong Li, Zhengxiang Jiang, Tianxiao Liu, Xinyu Liu, Hui Qiao, Xiaojun Yao:
Improving drug response prediction via integrating gene relationships with deep learning. - Haoquan Liu, Yunjie Zhao:
Integrated modeling of protein and RNA. - Zhenyu Wei, Chengkui Zhao, Min Zhang, Jiayu Xu, Nan Xu, Shiwei Wu, Xiaohui Xin, Lei Yu, Weixing Feng:
Meta-DHGNN: method for CRS-related cytokines analysis in CAR-T therapy based on meta-learning directed heterogeneous graph neural network. - Junxi Mu, Zhengxin Li, Bo Zhang, Qi Zhang, Jamshed Iqbal, Abdul Wadood, Ting Wei, Yan Feng, Hai-Feng Chen:
Graphormer supervised de novo protein design method and function validation. - Seunghyun Wang, Doheon Lee:
Community cohesion looseness in gene networks reveals individualized drug targets and resistance. - Zhen Gao, Yansen Su, Junfeng Xia, Rui-Fen Cao, Yun Ding, Chun-Hou Zheng, Pi-Jing Wei:
DeepFGRN: inference of gene regulatory network with regulation type based on directed graph embedding. - Xinyan Wang, Kuo Yang, Ting Jia, Fanghui Gu, Chongyu Wang, Kuan Xu, Zixin Shu, Jianan Xia, Qiang Zhu, Xuezhong Zhou:
KDGene: knowledge graph completion for disease gene prediction using interactional tensor decomposition. - Akram Vasighizaker, Sheena Hora, Raymond Zeng, Luis Rueda:
SEGCECO: Subgraph Embedding of Gene expression matrix for prediction of CEll-cell COmmunication. - Zhen Tian, Chenguang Han, Lewen Xu, Zhixia Teng, Wei Song:
MGCNSS: miRNA-disease association prediction with multi-layer graph convolution and distance-based negative sample selection strategy. - Priyotosh Sil, Ajay Subbaroyan, Saumitra Kulkarni, Olivier C. Martin, Areejit Samal:
Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph. - Correction to: Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.
- Chen Peng, Qiong Chen, Shangjin Tan, Xiaotao Shen, Chao Jiang:
Generalized reporter score-based enrichment analysis for omics data. - Zhao Peng, Jiaqiang Li, Xingpeng Jiang, Cuihong Wan:
sOCP: a framework predicting smORF coding potential based on TIS and in-frame features and effectively applied in the human genome. - Takashi Amisaki:
Multilevel superposition for deciphering the conformational variability of protein ensembles. - Huanhuan Liu, Qinwei Chen, Jintao Guo, Ying Zhou, Zhiyu You, Jun Ren, Yuanyuan Zeng, Jing Yang, Jialiang Huang, Qiyuan Li:
Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues. - Wang Yin, You Wan, Yuan Zhou:
SpatialcoGCN: deconvolution and spatial information-aware simulation of spatial transcriptomics data via deep graph co-embedding. - Xiao-Hong Ding, Yi Xiao, Fenfang Chen, Cheng-Lin Liu, Tong Fu, Zhi-Ming Shao, Yi-Zhou Jiang:
The HLA-I landscape confers prognosis and antitumor immunity in breast cancer. - Boya Ji, Haitao Zou, Liwen Xu, Xiaolan Xie, Shaoliang Peng:
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA-disease associations prediction. - Thomas G. Brooks, Nicholas F. Lahens, Antonijo Mrcela, Dimitra Sarantopoulou, Soumyashant Nayak, Amruta Naik, Shaon Sengupta, Peter S. Choi, Gregory R. Grant:
BEERS2: RNA-Seq simulation through high fidelity in silico modeling. - Ken Chen, Yue Zhou, Maolin Ding, Yu Wang, Zhixiang Ren, Yuedong Yang:
Self-supervised learning on millions of primary RNA sequences from 72 vertebrates improves sequence-based RNA splicing prediction. - Tram Huynh, Zixuan Cang:
Topological and geometric analysis of cell states in single-cell transcriptomic data. - Guoxuan Ma, Jian Kang, Tianwei Yu:
Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes. - Qiuhao Chen, Liyuan Zhang, Yaojia Liu, Zhonghao Qin, Tianyi Zhao:
PUTransGCN: identification of piRNA-disease associations based on attention encoding graph convolutional network and positive unlabelled learning. - Correction to: Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics.
- Zechen Wang, Sheng Wang, Yangyang Li, Jingjing Guo, Yanjie Wei, Yuguang Mu, Liangzhen Zheng, Weifeng Li:
A new paradigm for applying deep learning to protein-ligand interaction prediction. - Marc-Antoine Gerault, Samuel Granjeaud, Luc Camoin, Pär Nordlund, Lingyun Dai:
IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data. - Kongming Li, Jiahao Li, Yuhao Tao, Fei Wang:
stDiff: a diffusion model for imputing spatial transcriptomics through single-cell transcriptomics. - Le Zhang, Wenkai Song, Tinghao Zhu, Yang Liu, Wei Chen, Yang Cao:
ConvNeXt-MHC: improving MHC-peptide affinity prediction by structure-derived degenerate coding and the ConvNeXt model. - Hongyuan Zhao, Suyi Zhang, Hui Qin, Xiaogang Liu, Dongna Ma, Xiao Han, Jian Mao, Shuangping Liu:
DSNetax: a deep learning species annotation method based on a deep-shallow parallel framework. - Tinghe Zhang, Sumin Jo, Michelle Zhang, Kai Wang, Shou-Jiang Gao, Yufei Huang:
Understanding YTHDF2-mediated mRNA degradation by m6A-BERT-Deg. - Weihang Zhang, Yang Cui, Bowen Liu, Martin Loza, Sung-Joon Park, Kenta Nakai:
HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data. - Theinmozhi Arulraj, Hanwen Wang, Alberto Ippolito, Shuming Zhang, Elana J. Fertig, Aleksander S. Popel:
Leveraging multi-omics data to empower quantitative systems pharmacology in immuno-oncology. - Ming-Siang Huang, Jen-Chieh Han, Pei-Yen Lin, Yu-Ting You, Richard Tzong-Han Tsai, Wen-Lian Hsu:
Surveying biomedical relation extraction: a critical examination of current datasets and the proposal of a new resource. - Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li:
TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning. - Danel Olaverri-Mendizabal, Luis Vitores Valcarcel, Naroa Barrena, Carlos J. Rodríguez, Francisco J. Planes:
Review and meta-analysis of the genetic Minimal Cut Set approach for gene essentiality prediction in cancer metabolism. - Correction to: Inflated false discovery rate due to volcano plots: problem and solutions.
- Lixin Lei, Kaitai Han, Zijun Wang, Chaojing Shi, Zhenghui Wang, Ruoyan Dai, Zhiwei Zhang, Mengqiu Wang, Qianjin Guo:
Attention-guided variational graph autoencoders reveal heterogeneity in spatial transcriptomics. - Yue Kang, Hongyu Zhang, Jinting Guan:
scINRB: single-cell gene expression imputation with network regularization and bulk RNA-seq data. - Jinze Huang, Yang Zhao, Bo Meng, Ao Lu, Yaoguang Wei, Lianhua Dong, Xiang Fang, Dong An, Xinhua Dai:
SEAOP: a statistical ensemble approach for outlier detection in quantitative proteomics data. - Mingshuai Chen, Mingai Sun, Xi Su, Prayag Tiwari, Yijie Ding:
Fuzzy kernel evidence Random Forest for identifying pseudouridine sites. - Correction to: DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences.
- Adam Wright, Mark D. Wilkinson, Christopher J. Mungall, Scott Cain, Stephen Richards, Paul W. Sternberg, Ellen Provin, Jonathan L. Jacobs, Scott Geib, Daniela Raciti, Karen Yook, Lincoln Stein, David C. Molik:
FAIR Header Reference genome: a TRUSTworthy standard. - Zhanyu Xu, Haibo Liao, Liuliu Huang, Qingfeng Chen, Wei Lan, Shikang Li:
IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability. - Chunjiang Yu, Hui Zong, Yalan Chen, Yibin Zhou, Xingyun Liu, Yuxin Lin, Jiakun Li, Xiaonan Zheng, Hua Min, Bairong Shen:
PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data. - Xing Chen, Li Huang:
Computational model for drug research. - Zhaojia Chen, Noor ul Ain, Qian Zhao, Xingtan Zhang:
From tradition to innovation: conventional and deep learning frameworks in genome annotation. - Conghao Wang, Hiok Hian Ong, Shunsuke Chiba, Jagath C. Rajapakse:
GLDM: hit molecule generation with constrained graph latent diffusion model. - Shenjie Wang, Xiaoyan Zhu, Xuwen Wang, Yuqian Liu, Minchao Zhao, Zhili Chang, Xiaonan Wang, Yang Shao, Jiayin Wang:
TMBstable: a variant caller controls performance variation across heterogeneous sequencing samples.
Volume 25, Number 4, 2024
- Simin Xia, Dianke Li, Xinru Deng, Zhongyang Liu, Huaqing Zhu, Yuan Liu, Dong Li:
Integration of protein sequence and protein-protein interaction data by hypergraph learning to identify novel protein complexes. - Eduardo N. Castanho, Helena Aidos, Sara C. Madeira:
Biclustering data analysis: a comprehensive survey. - Qiaosi Tang, Ranjala Ratnayake, Gustavo de M. Seabra, Zhe Jiang, Ruogu Fang, Lina Cui, Yousong Ding, Tamer Kahveci, Jiang Bian, Chenglong Li, Hendrik Luesch, Yanjun Li:
Morphological profiling for drug discovery in the era of deep learning. - Ran Jia, Ying-Zan Ren, Po-Nian Li, Rui Gao, Yusen Zhang:
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition. - Yanli Wang, Jianlin Cheng:
HiCDiff: single-cell Hi-C data denoising with diffusion models. - Lequn Wang, Yaofeng Hu, Kai Xiao, Chuanchao Zhang, Qianqian Shi, Luonan Chen:
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics. - Sudipto Baul, Khandakar Tanvir Ahmed, Qibing Jiang, Guangyu Wang, Qian Li, Jeongsik Yong, Wei Zhang:
Integrating spatial transcriptomics and bulk RNA-seq: predicting gene expression with enhanced resolution through graph attention networks. - Chengshang Lyu, Lingxi Chen, Xiaoping Liu:
Detecting tipping points of complex diseases by network information entropy. - Yue Li, Bingyan Liu, Jinyan Deng, Yi Guo, Hongbo Du:
Image-based molecular representation learning for drug development: a survey. - Bijia Chen, Chao Ren, Zhangyi Ouyang, Jingxuan Xu, Kang Xu, Yaru Li, Hejiang Guo, Xuemei Bai, Mengge Tian, Xiang Xu, Yuyang Wang, Hao Li, Xiaochen Bo, Hebing Chen:
Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair. - Hongtai Jing, Zhengtao Gao, Sheng Xu, Tao Shen, Zhangzhi Peng, Shwai He, Tao You, Shuang Ye, Wei Lin, Siqi Sun:
Accurate prediction of antibody function and structure using bio-inspired antibody language model. - Georg Hahn, Dmitry Prokopenko, Julian Hecker, Sharon Marie Lutz, Kristina Mullin, Leinal Sejour, Winston Hide, Ioannis Vlachos, Stacia Desantis, Rudolph E. Tanzi, Christoph Lange:
Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data. - Guoqiang Zhou, Yuke Qin, Qiansen Hong, Haoran Li, Huaming Chen, Jun Shen:
GEMF: a novel geometry-enhanced mid-fusion network for PLA prediction. - Sarthak Jain, Sandra E. Safo:
DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification. - Qingxiong Tan, Jin Xiao, Jiayang Chen, Yixuan Wang, Zeliang Zhang, Tiancheng Zhao, Yu Li:
ifDEEPre: large protein language-based deep learning enables interpretable and fast predictions of enzyme commission numbers. - Lixin Ren, Wanbiao Ma, Yong Wang:
Predicting RNA polymerase II transcriptional elongation pausing and associated histone code. - Skylar A Gay, Gregory Ellison, Jianing Xu, Jialin Yang, Yiliang Wei, Shaoyuan Wu, Lili Yu, Christopher C. Whalen, Jonathan Arnold, Liang Liu:
Phylogenetic inference of inter-population transmission rates for infectious diseases. - Qiang Yang, Long Xu, Weihe Dong, Xiaokun Li, Kuanquan Wang, Suyu Dong, Xianyu Zhang, Tiansong Yang, Feng Jiang, Bin Zhang, Gongning Luo, Xin Gao, Guohua Wang:
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses. - Ru Zhang, Yanmei Lin, Yijia Wu, Lei Deng, Hao Zhang, Mingzhi Liao, Yuzhong Peng:
MvMRL: a multi-view molecular representation learning method for molecular property prediction. - Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Wenliang Zhong, Yi Han, Tao Wang, Junzhou Huang:
GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity. - Joshua Beals, Haiyan Hu, Xiaoman Li:
A survey of experimental and computational identification of small proteins. - Xiangru Tang, Howard Dai, Elizabeth Knight, Fang Wu, Yunyang Li, Tianxiao Li, Mark Gerstein:
A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation. - Lei Li, Jiayi Sun, Yanbin Fu, Siriruk Changrob, Joshua J. C. McGrath, Patrick C. Wilson:
A hybrid demultiplexing strategy that improves performance and robustness of cell hashing. - Zhihao Si, Hanshuang Li, Wenjing Shang, Yanan Zhao, Lingjiao Kong, Chunshen Long, Yongchun Zuo, Zhenxing Feng:
SpaNCMG: improving spatial domains identification of spatial transcriptomics using neighborhood-complementary mixed-view graph convolutional network. - Ao Shen, Mingzhi Yuan, Yingfan Ma, Jie Du, Manning Wang:
Complementary multi-modality molecular self-supervised learning via non-overlapping masking for property prediction. - Haiping Zhang, Hongjie Fan, Jixia Wang, Tao Hou, Konda Mani Saravanan, Wei Xia, Hei Wun Kan, Junxin Li, John Z. H. Zhang, Xinmiao Liang, Yang Chen:
Revolutionizing GPCR-ligand predictions: DeepGPCR with experimental validation for high-precision drug discovery. - Jun Teng, Tingting Zhai, Xinyi Zhang, Changheng Zhao, Wenwen Wang, Hui Tang, Dan Wang, Yingli Shang, Chao Ning, Qin Zhang:
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information. - Steven Allers, Kyle A. O'Connell, Thad B. Carlson, David Belardo, Benjamin L. King:
Reusable tutorials for using cloud-based computing environments for the analysis of bacterial gene expression data from bulk RNA sequencing. - Md. Mamunur Rashid, Kumar Selvarajoo:
Advancing drug-response prediction using multi-modal and -omics machine learning integration (MOMLIN): a case study on breast cancer clinical data. - Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model.
- Jing-Tian Wang, Xiao-Yu Chang, Qiong Zhao, Yuan-Ming Zhang:
FastBiCmrMLM: a fast and powerful compressed variance component mixed logistic model for big genomic case-control genome-wide association study. - Alen Suljic, Tomaz Mark Zorec, Samo Zakotnik, Doroteja Vlaj, Rok Kogoj, Natasa Knap, Miroslav Petrovec, Mario Poljak, Tatjana Avsic-Zupanc, Misa Korva:
Efficient SARS-CoV-2 variant detection and monitoring with Spike Screen next-generation sequencing. - Zhengfa Xue, Aifen Zhou, Xiaoyan Zhu, Linxuan Li, Huanhuan Zhu, Xin Jin, Jiayin Wang:
NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach. - Jiashuo Wu, Xilong Zhao, Yalan He, Bingyue Pan, Jiyin Lai, Miao Ji, Siyuan Li, Junling Huang, Junwei Han:
IDMIR: identification of dysregulated miRNAs associated with disease based on a miRNA-miRNA interaction network constructed through gene expression data. - Siwen Wu, Jun-tao Guo:
Improved prediction of DNA and RNA binding proteins with deep learning models. - Christophe Boetto, Arthur Frouin, Léo Henches, Antoine Auvergne, Yuka Suzuki, Etienne Patin, Marius Bredon, Alec Chiu, Milieu Interieur Consortium, Sriram Sankararaman, Noah Zaitlen, Sean P. Kennedy, Lluis Quintana-Murci, Darragh Duffy, Harry Sokol, Hugues Aschard:
MANOCCA: a robust and computationally efficient test of covariance in high-dimension multivariate omics data. - Junyao Jiang, Jinlian Li, Sunan Huang, Fan Jiang, Yanran Liang, Xueli Xu, Jie Wang:
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data. - Shengbo Wu, Haonan Zhou, Danlei Chen, Yutong Lu, Yanni Li, Jianjun Qiao:
Multi-omic analysis tools for microbial metabolites prediction. - Jacob J. E. Koopman, Katherine A Buhler, May Y. Choi:
From machine learning to clinical practice: phenotypic clusters of anti-MDA5 antibody-positive dermatomyositis. - Jilong Bian, Hao Lu, Guanghui Dong, Guohua Wang:
Hierarchical multimodal self-attention-based graph neural network for DTI prediction. - Pi-Jing Wei, Ziqiang Guo, Zhen Gao, Zheng Ding, Rui-Fen Cao, Yansen Su, Chun-Hou Zheng:
Inference of gene regulatory networks based on directed graph convolutional networks. - Qirui Guo, Musu Yuan, Lei Zhang, Minghua Deng:
scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement. - Liang Cheng:
Attention mechanism models for precision medicine. - Euiseong Ko, Youngsoon Kim, Farhad Shokoohi, Tesfaye B. Mersha, Mingon Kang:
SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis. - Weibing Wang, Yusen Ye, Lin Gao:
Statistical modeling and significance estimation of multi-way chromatin contacts with HyperloopFinder. - Baohui Lin, Xiaoling Luo, Yumeng Liu, Xiaopeng Jin:
A comprehensive review and comparison of existing computational methods for protein function prediction. - Emily McLeish, Nataliya Slater, Frank L. Mastaglia, Merrilee Needham, Jerome D. Coudert:
Balancing Clinical Applicability and Scientific Depth in ML Models for MDA5-DM Prognosis. - Yujin Kim, Minwoo Jeong, In Gyeong Koh, Chanhee Kim, Hyeji Lee, Jae Hyun Kim, Ronald Yurko, Il Bin Kim, Jeongbin Park, Donna M. Werling, Stephan J. Sanders, Joon-Yong An:
CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data. - Mengxin Zheng, Guicong Sun, Xueping Li, Yongxian Fan:
EGPDI: identifying protein-DNA binding sites based on multi-view graph embedding fusion. - Jaeyoon Kim, Junhee Seok:
ctGAN: combined transformation of gene expression and survival data with generative adversarial network. - Zihan Dong, Wei Jiang, Hongyu Li, Andrew T. Dewan, Hongyu Zhao:
LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information. - Xinjia Ruan, Yu Cheng, Yuqing Ye, Yuhang Wang, Xinyi Chen, Yuqing Yang, Tiantian Liu, Fangrong Yan:
PIPET: predicting relevant subpopulations in single-cell data using phenotypic information from bulk data. - Heng Hu, Runtian Gao, Wentao Gao, Bo Gao, Zhongjun Jiang, Murong Zhou, Guohua Wang, Tao Jiang:
SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies. - Ryan P. Seaman, Ross Campbell, Valena Doe, Zelaikha Yosufzai, Joel H. Graber:
A cloud-based training module for efficient de novo transcriptome assembly using Nextflow and Google cloud. - Sara Joubbi, Alessio Micheli, Paolo Milazzo, Giuseppe Maccari, Giorgio Ciano, Dario Cardamone, Duccio Medini:
Antibody design using deep learning: from sequence and structure design to affinity maturation. - Regina Nóra Fiam, Csabai István, Solymosi Norbert:
Comparing full variation profile analysis with the conventional consensus method in SARS-CoV-2 phylogeny. - Ali H. Rafati, Sâmia Joca, Regina T. Vontell, Gregers Wegener, Maryam Ardalan:
Approaches to embryonic neurodevelopment: from neural cell to neural tube formation through mathematical models. - Han Wang, Chang Li, Xinyu Yu, Jingyang Gao:
Deletion variants calling in third-generation sequencing data based on a dual-attention mechanism. - Paolo Battuello, Giorgio Corti, Alice Bartolini, Annalisa Lorenzato, Alberto Sogari, Mariangela Russo, Federica Di Nicolantonio, Alberto Bardelli, Giovanni Crisafulli:
Mutational signatures of colorectal cancers according to distinct computational workflows. - Hwiyoung Lee, Tianzhou Ma, Hongjie Ke, Zhenyao Ye, Shuo Chen:
dCCA: detecting differential covariation patterns between two types of high-throughput omics data. - Maria A Rujano, Jan-Willem Boiten, Christian Ohmann, Steve Canham, Sergio Contrino, Romain David, Jonathan Ewbank, Claudia Filippone, Claire Connellan, Ilse Custers, Rick van Nuland, Michaela Theresia Mayrhofer, Petr Holub, Eva García Álvarez, Emmanuel Bacry, Nigel Hughes, Mallory Ann Freeberg, Birgit Schaffhauser, Harald Wagener, Alex Sánchez-Pla, Guido Bertolini, Maria Panagiotopoulou:
Sharing sensitive data in life sciences: an overview of centralized and federated approaches. - Sandeep Singh, Xinrui Shi, Samuel Haddox, Justin Elfman, Syed Basil Ahmad, Sarah Lynch, Tommy Manley, Claire Piczak, Christopher Phung, Yunan Sun, Aadi Sharma, Hui Li:
RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data. - Asif M. Khan, Esra Büsra Isik, Tin Wee Tan:
A global initiative on addressing bioinformatics' grand challenges. - Zeqian Li, Shilong Wang, Hai Cui, Xiaoxia Liu, Yijia Zhang:
Spatiotemporal constrained RNA-protein heterogeneous network for protein complex identification. - Meihui Tian, Weifang Sun, Yinhui Mao, Yanan Zhang, Huan Liu, Yong Tang:
Mechanistic study of acupuncture on the pterygopalatine ganglion to improve allergic rhinitis: analysis of multi-target effects based on bioinformatics/network topology strategie. - Ishtiaque Ahammad, Anika Bushra Lamisa, Arittra Bhattacharjee, Tabassum Binte Jamal, Md Shamsul Arefin, Zeshan Mahmud Chowdhury, Mohammad Uzzal Hossain, Keshob Chandra Das, Chaman Ara Keya, Md. Salimullah:
AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature. - Catalina Gonzalez Gomez, Manuel Rosa-Calatrava, Julien Fouret:
Optimizing in silico drug discovery: simulation of connected differential expression signatures and applications to benchmarking. - Yuan Gao, Bin Ma, Qianshuai Xu, Yuna Peng, Huimin Gong, Aohan Guan, Kexin Hua, Paul R. Langford, Hui Jin, Rui Luo:
Spatial proximity and gene function: a new dimension in prokaryotic gene association network analysis with 3D-GeneNet. - Juok Cho, Bukyung Baik, Hai C. T. Nguyen, Daeui Park, Dougu Nam:
Characterizing efficient feature selection for single-cell expression analysis. - Michal Zawisza-Álvarez, Jesús Peñuela-Melero, Esteban Vegas, Ferran Reverter, Jordi Garcia-Fernàndez, Carlos Herrera-Úbeda:
Exploring functional conservation in silico: a new machine learning approach to RNA-editing. - En-Yu Lai, Yen-Tsung Huang:
Identifying pleiotropic genes via the composite test amidst the complexity of polygenic traits. - Sagar Gupta, Veerbhan Kesarwani, Umesh Bhati, Jyoti, Ravi Shankar:
PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants. - Lei Zhang, Shu Liang, Lin Wan:
A multi-view graph contrastive learning framework for deciphering spatially resolved transcriptomics data. - Rajan Gyawali, Ashwin Dhakal, Liguo Wang, Jianlin Cheng:
CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net. - Mostafa Herajy, Fei Liu, Monika Heiner:
Design patterns for the construction of computational biological models. - Quyuan Tao, Yiheng Xu, Youzhe He, Ting Luo, Xiaoming Li, Lei Han:
Benchmarking mapping algorithms for cell-type annotating in mouse brain by integrating single-nucleus RNA-seq and Stereo-seq data. - Alexei Novoloaca, Camilo Broc, Laurent Beloeil, Wen-Han Yu, Jérémie Becker:
Comparative analysis of integrative classification methods for multi-omics data. - Junbo Duan, Xinrui Zhao, Xiaoming Wu:
LoRA-TV: read depth profile-based clustering of tumor cells in single-cell sequencing. - Nanjun Chen, Jixiang Yu, Zhe Liu, Fuzhou Wang, Xiangtao Li, Ka-Chun Wong:
TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation. - Guoqing Zhang, Hui Wang, Zhiguo Zhang, Lu Zhang, Guibing Guo, Jian Yang, Fajie Yuan, Feng Ju:
Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework. - Hegang Chen, Yuyin Lu, Zhiming Dai, Yuedong Yang, Qing Li, Yanghui Rao:
Comprehensive single-cell RNA-seq analysis using deep interpretable generative modeling guided by biological hierarchy knowledge. - Tao Wang, Han Shu, Jialu Hu, Yongtian Wang, Jin Chen, Jiajie Peng, Xuequn Shang:
Accurately deciphering spatial domains for spatially resolved transcriptomics with stCluster. - Yahui Lei, Xiao-Tai Huang, Xingli Guo, Kei Hang Katie Chan, Lin Gao:
DeepGRNCS: deep learning-based framework for jointly inferring gene regulatory networks across cell subpopulations. - Aleksandr Ianevski, Aleksandr Kushnir, Kristen Nader, Mitro Miihkinen, Henri Xhaard, Tero Aittokallio, ZiaurRehman Tanoli:
RepurposeDrugs: an interactive web-portal and predictive platform for repurposing mono- and combination therapies. - Correction to: Prediction of protein-ligand binding affinity via deep learning models.
- Yue Xi, Kun Zheng, Fulan Deng, Yujun Liu, Hourong Sun, Yingxia Zheng, Henry H. Y. Tong, Yuan Ji, Yingchun Zhang, Wantao Chen, Yiming Zhang, Xin Zou, Jie Hao:
Themis: advancing precision oncology through comprehensive molecular subtyping and optimization. - Bowen Li, Zhen Wang, Ziqi Liu, Yanxin Tao, Chulin Sha, Min He, Xiaolin Li:
DrugMetric: quantitative drug-likeness scoring based on chemical space distance. - Miguel Hernandez-Gamarra, Alba Salgado-Roo, Eduardo Dominguez, Elena María Goiricelaya Seco, Sara Veiga-Rúa, Lucía F. Pedrera-Garbayo, Ángel Carracedo, Catarina Allegue:
CARTAR: a comprehensive web tool for identifying potential targets in chimeric antigen receptor therapies using TCGA and GTEx data. - Dezhen Zhang, Shuhua Gao, Zhi-Ping Liu, Rui Gao:
LogicGep: Boolean networks inference using symbolic regression from time-series transcriptomic profiling data. - Leandro A Bugnon, Leandro E. Di Persia, Matias Gerard, Jonathan Raad, Santiago Prochetto, Emilio Fenoy, Uciel Chorostecki, Federico Ariel, Georgina Stegmayer, Diego H. Milone:
sincFold: end-to-end learning of short- and long-range interactions in RNA secondary structure. - Guangyu Li, Jiayu Wu, Xiaoyue Wang:
Predicting functional UTR variants by integrating region-specific features. - Lea Eckhart, Kerstin Lenhof, Lisa-Marie Rolli, Hans-Peter Lenhof:
A comprehensive benchmarking of machine learning algorithms and dimensionality reduction methods for drug sensitivity prediction. - Chuiqin Fan, Fuyi Chen, Yuanguo Chen, Liangping Huang, Manna Wang, Yulin Liu, Yu Wang, Huijie Guo, Nanpeng Zheng, Yanbing Liu, Hongwu Wang, Lian Ma:
irGSEA: the integration of single-cell rank-based gene set enrichment analysis. - Ruofan Jin, Qing Ye, Jike Wang, Zheng Cao, Dejun Jiang, Tianyue Wang, Yu Kang, Wanting Xu, Chang-Yu Hsieh, Tingjun Hou:
AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences. - Renmao Tian, Jizhong Zhou, Behzad Imanian:
PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning. - Gregory Tong, Nasun Hah, Thomas F. Martinez:
Comparison of software packages for detecting unannotated translated small open reading frames by Ribo-seq. - Raghvendra Mall, Ankita Singh, Chirag N. Patel, Gregory Guirimand, Filippo Castiglione:
VISH-Pred: an ensemble of fine-tuned ESM models for protein toxicity prediction. - Wenkai Xiang, Feisheng Zhong, Lin Ni, Mingyue Zheng, Xutong Li, Qian Shi, Dingyan Wang:
Gram matrix: an efficient representation of molecular conformation and learning objective for molecular pretraining. - Cheng Zhu, Chengyun Zhang, Tianfeng Shang, Chenhao Zhang, Silong Zhai, Lujing Cao, Zhenyu Xu, Zhihao Su, Ying Song, An Su, Chengxi Li, Hongliang Duan:
GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach. - Montserrat Goles, Anamaria Sanchez-Daza, Gabriel Cabas-Mora, Lindybeth Sarmiento-Varón, Julieta Sepúlveda-Yañez, Hoda Anvari-Kazemabad, Mehdi D. Davari, Roberto Uribe Paredes, Alvaro Olivera-Nappa, Marcelo A. Navarrete, David Medina-Ortiz:
Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides. - Runzhou Yu, Ziyi Huang, Theo Y. C. Lam, Yanni Sun:
Utilizing profile hidden Markov model databases for discovering viruses from metagenomic data: a comprehensive review. - Onder Tutsoy, Hilmi Erdem Sumbul:
A novel deep machine learning algorithm with dimensionality and size reduction approaches for feature elimination: thyroid cancer diagnoses with randomly missing data.
Volume 25, Number 5, 2024
- Aishwarya Budhkar, Ziyang Tang, Xiang Liu, Xuhong Zhang, Jing Su, Qianqian Song:
xSiGra: explainable model for single-cell spatial data elucidation. - Linlin Hou, Hongxin Xiang, Xiangxiang Zeng, Dongsheng Cao, Li Zeng, Bosheng Song:
Attribute-guided prototype network for few-shot molecular property prediction. - Qitao Jia, Yuanling Xia, Fanglin Dong, Weihua Li:
MetaFluAD: meta-learning for predicting antigenic distances among influenza viruses. - Wentao Cui, Qingqing Long, Meng Xiao, Xuezhi Wang, Guihai Feng, Xin Li, Pengfei Wang, Yuanchun Zhou:
Refining computational inference of gene regulatory networks: integrating knockout data within a multi-task framework. - Zeyu Lu, Xue Xiao, Qiang Zheng, Xinlei Wang, Lin Xu:
Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets. - Xinze Liu, Jingxuan Shi, Yuanyuan Jiao, Jiaqi An, Jingwei Tian, Yue Yang, Li Zhuo:
Integrated multi-omics with machine learning to uncover the intricacies of kidney disease. - Lei Chen, Jiahui Gu, Bo Zhou:
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs. - Yida Wu, Da Zhou, Jie Hu:
Reconstruction of gene regulatory networks for Caenorhabditis elegans using tree-shaped gene expression data. - Kerstin Lenhof, Lea Eckhart, Lisa-Marie Rolli, Hans-Peter Lenhof:
Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer. - Fenglei Li, Qiaoyu Hu, Yongqi Zhou, Hao Yang, Fang Bai:
DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras. - Yang Xu, Yuxiang Zhang, Yanru Cui, Kai Zhou, Guangning Yu, Wenyan Yang, Xin Wang, Furong Li, Xiusheng Guan, Xuecai Zhang, Zefeng Yang, Shizhong Xu, Chenwu Xu:
GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection. - Weihong Huang, Feng Yang, Qiang Zhang, Juan Liu:
A dual-scale fused hypergraph convolution-based hyperedge prediction model for predicting missing reactions in genome-scale metabolic networks. - Katarzyna Nalecz-Charkiewicz, Kamil Charkiewicz, Robert M. Nowak:
Quantum computing in bioinformatics: a systematic review mapping. - Marwan Abdellah, Alessandro Foni, Juan Jose Garcia-Cantero, Nadir Román Guerrero, Elvis Boci, Adrien Fleury, Jay S. Coggan, Daniel Keller, Judit Planas, Jean-Denis Courcol, Georges Khazen:
Synthesis of geometrically realistic and watertight neuronal ultrastructure manifolds for in silico modeling. - Harrison Anthony, Cathal Seoighe:
Performance assessment of computational tools to detect microsatellite instability. - Yiran Huang, Yufu Lin, Wei Lan, Cuiyu Huang, Cheng Zhong:
GloEC: a hierarchical-aware global model for predicting enzyme function. - Xinglong Wang, Kangjie Xu, Xuan Zeng, Kai Linghu, Beichen Zhao, Shangyang Yu, Kun Wang, Shuyao Yu, Xinyi Zhao, Weizhu Zeng, Kai Wang, Jingwen Zhou:
Machine learning-assisted substrate binding pocket engineering based on structural information. - Weining Lu, Yin Tang, Yu Liu, Shiyi Lin, Qifan Shuai, Bin Liang, Rongqing Zhang, Yu Cheng, Dong Fang:
CatLearning: highly accurate gene expression prediction from histone mark. - Benjamin Tam, Philip Naderev P. Lagniton, Mariano Da Luz, Bojin Zhao, Siddharth Sinha, Chon Lok Lei, San Ming Wang:
Comprehensive classification of TP53 somatic missense variants based on their impact on p53 structural stability. - Zhaohan Meng, Siwei Liu, Shangsong Liang, Bhautesh Jani, Zaiqiao Meng:
Heterogeneous biomedical entity representation learning for gene-disease association prediction. - Shunjie Zhang, Pan Li, Shenghan Wang, Jijun Zhu, Zhongting Huang, Fuqiang Cai, Sebastian Freidel, Fei Ling, Emanuel Schwarz, Junfang Chen:
BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data. - Noura Aherrahrou, Hamid Tairi, Zouhair Aherrahrou:
Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision. - Xinhao Yi, Siwei Liu, Yu Wu, Douglas McCloskey, Zaiqiao Meng:
BPP: a platform for automatic biochemical pathway prediction. - James S. L. Browning Jr., Daniel R. Tauritz, John Beckmann:
Evolutionary algorithms simulating molecular evolution: a new field proposal. - Yan Miao, Zhenyuan Sun, Chen Lin, Haoran Gu, Chenjing Ma, Yingjian Liang, Guohua Wang:
DeePhafier: a phage lifestyle classifier using a multilayer self-attention neural network combining protein information. - Vijini Mallawaarachchi, Anuradha Wickramarachchi, Hansheng Xue, Bhavya Nalagampalli Papudeshi, Susanna R. Grigson, George Bouras, Rosa E. Prahl, Anubhav Kaphle, Andrey Verich, Berenice Talamantes-Becerra, Elizabeth A. Dinsdale, Robert A. Edwards:
Solving genomic puzzles: computational methods for metagenomic binning. - Correction to: Accurate prediction of antibody function and structure using bio-inspired antibody language model.
- Yuxing Wang, Junhan Zhao, Hongye Xu, Cheng Han, Zhiqiang Tao, Dawei Zhou, Tong Geng, Dongfang Liu, Zhicheng Ji:
A systematic evaluation of computational methods for cell segmentation. - Ruohan Ren, Hongyu Yu, Jiahao Teng, Sihui Mao, Zixuan Bian, Yangtianze Tao, Stephen S.-T. Yau:
CAPE: a deep learning framework with Chaos-Attention net for Promoter Evolution. - Zhenze Liu, Yingjian Liang, Guohua Wang, Tianjiao Zhang:
scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data. - Liang Liu, Peiqing Sun, Wei Zhang:
A pan-cancer interrogation of intronic polyadenylation and its association with cancer characteristics. - Keyun Zhu, Mengting Huang, Yimeng Wang, Yaxin Gu, Weihua Li, Guixia Liu, Yun Tang:
MetaPredictor: in silico prediction of drug metabolites based on deep language models with prompt engineering. - Chang Dou, Yijie Yang, Fei Zhu, Bingzhi Li, Yuping Duan:
Explorer: efficient DNA coding by De Bruijn graph toward arbitrary local and global biochemical constraints. - Yuefan Lin, Zixiang Pan, Yuansong Zeng, Yuedong Yang, Zhiming Dai:
Detecting novel cell type in single-cell chromatin accessibility data via open-set domain adaptation. - Suronjit Kumar Roy, Mohammad Shahangir Biswas, Md Foyzur Raman, Rubait Hasan, Zahidur Rahmann, Md Moyen Uddin Pk:
A computational approach to developing a multi-epitope vaccine for combating Pseudomonas aeruginosa-induced pneumonia and sepsis. - Xiaobao Ding, Lin Zhang, Ming Fan, Lihua Li:
TME-NET: an interpretable deep neural network for predicting pan-cancer immune checkpoint inhibitor responses. - Yinyin Wang, Yihang Sui, Jiaqi Yao, Hong Jiang, Qimeng Tian, Yun Tang, Yongyu Ou, Jing Tang, Ninghua Tan:
Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study. - Margarita Pertseva, Oceane Follonier, Daniele Scarcella, Sai T. Reddy:
TCR clustering by contrastive learning on antigen specificity. - Jingjing Wang, Zhijiang Yang, Chang Chen, Ge Yao, Xiukun Wan, Shaoheng Bao, Junjie Ding, Liangliang Wang, Hui Jiang:
MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction. - Young Su Ko, Jonathan Parkinson, Cong Liu, Wei Wang:
TUnA: an uncertainty-aware transformer model for sequence-based protein-protein interaction prediction. - Yang Li, Anjun Ma, Yizhong Wang, Qi Guo, Cankun Wang, Hongjun Fu, Bingqiang Liu, Qin Ma:
Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data. - Feng Li, Jingwen Wang, Mengyue Li, Xiaomeng Zhang, Yongjuan Tang, Xinyu Song, Yifang Zhang, Liying Pei, Jiaqi Liu, Chunlong Zhang, Xia Li, Yanjun Xu, Yunpeng Zhang:
Identifying cell type-specific transcription factor-mediated activity immune modules reveal implications for immunotherapy and molecular classification of pan-cancer. - Qiqing Fu, Chenyu Dong, Yunhe Liu, Xiaoqiong Xia, Gang Liu, Fan Zhong, Lei Liu:
A comparison of scRNA-seq annotation methods based on experimentally labeled immune cell subtype dataset. - Correction to: Revolutionizing GPCR-ligand predictions: DeepGPCR with experimental validation for high-precision drug discovery.
Volume 25, Number 6, 2024
- Yabin Kuang, Minzhu Xie:
DrugDoctor: enhancing drug recommendation in cold-start scenario via visit-level representation learning and training. - Aliaa E. Ali, Li-Li Li, Michael J. Courtney, Olli T. Pentikäinen, Pekka A. Postila:
Atomistic simulations reveal impacts of missense mutations on the structure and function of SynGAP1. - Musaddiq K. Lodi, Anna Chernikov, Preetam Ghosh:
COFFEE: consensus single cell-type specific inference for gene regulatory networks.
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-11-11 21:32 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
