Best Genomics Data Analysis Software

JADBio is a state-of-the-art automated Machine Learning Platform without the need for coding. With its breakthrough algorithms it can solve open problems in machine learning. Anybody can use it and perform a sophisticated and correct machine learning analysis even if they do not know any math, statistics, or coding. It is purpose-built for life science data and particularly molecular data. This means that it can deal with the idiosyncrasies of molecular data such as very low sample size and very high number of measured quantities that could reach to millions. Life scientists need it to understand what are the features and biomarkers that are predictive and important, what is their role, and get intuition about the molecular mechanisms involved. Knowledge discovery is often more important than a predictive model. So, JADBio focuses on feature selection and its interpretation.

ESMFold shows how AI can give us new tools to understand the natural world, much like the microscope, which enabled us to see into the world at an infinitesimal scale and opened up a whole new understanding of life. AI can help us understand the immense scope of natural diversity, and see biology in a new way. Much of AI research has focused on helping computers understand the world in a way similar to how humans do. The language of proteins is one that is beyond human comprehension and has eluded even the most powerful computational tools. AI has the potential to open up this language to our understanding. Studying AI in new domains such as biology can also give insight into artificial intelligence more broadly. Our work reveals connections across domains: large language models that are behind advances in machine translation, natural language understanding, speech recognition, and image generation are also able to learn deep information about biology.

Jinni's taste-based content-to-audience platform provides revolutionary personalization solutions for video content discovery and targeted digital advertising for entertainment brands. Through its unique Entertainment Genome™, consisting of thousands of distinct content attributes or "genes", Jinni not only understands the most subtle differences in TV and movie entertainment content but also understands each individual's unique entertainment tastes, thereby providing the perfect match between individual and content titles! Our mission is to be the best-in-class content-to-audience platform for entertainment brands, using one platform to match & promote entertainment content to the right audiences, dramatically increasing profitability for platform operators and entertainment advertisers. Jinni's semantic algorithms that match content to users' personal tastes have been setting the direction for the next generation of content discovery & recommendations for the industry.

Clara’s domain-specific tools, AI pre-trained models, and accelerated applications are enabling AI breakthroughs in numerous fields, including medical devices, imaging, drug discovery, and genomics. Explore the end-to-end pipeline of medical device development and deployment with the Holoscan platform. Build containerized AI apps with the Holoscan SDK and MONAI, and streamline deployment in next-generation AI devices with the NVIDIA IGX developer kits. The NVIDIA Holoscan SDK includes healthcare-specific acceleration libraries, pre-trained AI models, and reference applications for computational medical devices.

Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.

Securely combine the multiomic data of individuals with their medical history to deliver more personalized care. Use purpose-built data stores to support large-scale analysis and collaborative research across entire populations. Accelerate research by using scalable workflows and integrated computation tools. Protect patient privacy with HIPAA eligibility and built-in data access and logging. AWS HealthOmics helps healthcare and life science organizations and their software partners store, query, and analyze genomic, transcriptomic, and other omics data and then generate insights from that data to improve health and advance scientific discoveries. Store and analyze omics data for hundreds of thousands of patients to understand how omics variation maps to phenotypes across a population. Build reproducible and traceable clinical multiomics workflows to reduce turnaround times and increase productivity. Integrate multiomic analysis into clinical trials to test new drug candidates.