Artificial intelligence’s incorporation has become a paradigm shifter in the dynamic field of biological research. Artificial intelligence (AI) powered tools are revolutionizing bioinformatics, helping to speed up drug development and decipher genomic puzzles. Here are the top AI tools for genomics, drug discovery, and machine learning ML.
Google’s variant-calling tool is DeepVariant. This analysis pipeline extracts genetic variations from data generated by next-generation DNA sequencing using a deep neural network.
Genomic data management using the cloud is DNAnexus. The Precision Health Data Cloud allows biomedical firms to speed scientific discovery and enhance patient care.
The Rosetta software suite encompasses protein structural analysis and computational modeling. It has made notable scientific advancements in computational biology possible, such as the creation of enzymes and proteins from scratch, the docking of ligands, and the prediction of the structures of biological macromolecules and complexes.
Bionano’s VIA is the only analysis program that receives and interprets data from microarrays, next-generation sequencing (NGS), and optical genome mapping (OGM) to contextualize all kinds of genomic variation and create significant insights.
Bioinformatics data driven by artificial intelligence is housed in Illumina’s DRAGEN platform. All labs, no matter how big or little, can benefit from DRAGEN secondary analysis, a robust bioinformatics software suite.
PathAI is an AI-powered field that aids in the diagnosis of cancer. The technology ensures that patients have access to precise diagnoses and efficient treatments. It is powered by artificial intelligence and is the result of meaningful collaboration between biopharma, laboratories, and clinicians.
Seven Bridges is a biological data analysis firm speeding up progress in precision medicine, cancer genomes, and drug discovery. It is a bioinformatics platform that incorporates AI capabilities for genomics studies.
VarSome is an AI-driven tool for interpreting variants. It serves as a platform for discovering variants, aggregating data, and building a community of variant expertise.
If you’re looking for artificial intelligence solutions for preclinical research and development, look no further than BenchSci. We use unique technologies to help decipher the complexity of biomedical research.
Parabricks, a free software suite, can be used for secondary analysis of DNA and RNA data from next-generation sequencing (NGS). Genomics analysis has been expedited by utilizing GPU-based parallel computing.
The Biocellion platform mimics cellular activity using artificial intelligence. Biocellion’s digital twin, YAcc (Yield Accelerator), will aid cellular agricultural businesses in increasing output and turning a profit.
The deep learning system that can use genome sequencing to predict phenotype is DeepMetabolism. It incorporates supervised and unsupervised learning into its neural network model, which it builds using biological knowledge to make predictions.
Using artificial intelligence, Basepair analyzes next-generation sequencing (NGS) data. Its cutting-edge platform can be used by researchers in the academic, business, and medical fields.
Using data-driven methods like machine learning and high-throughput biology, insitro is revolutionizing the pharmaceutical industry.
By assisting actual scientists in being more productive and making better use of resources (both financial and human), Tinybio has become the first genomic generative AI firm. Analyze your microbiome and metagenomics with the help of AI solutions.
When it comes to functional genomics, BioBam has you covered with its AI-powered solutions. BioBam is an industry-leading bioinformatics company that speeds up research in many fields, including agricultural genomics, environmental NGS studies, microbiology, and more. BioBam is all about easy-to-use software solutions for biological research.
At MedGenome, we use AI to perform genomics research and diagnosis. MedGenome is a worldwide provider of multiomics solutions to help you advance your genomics research and medication development.
PetaGene employs AI to organize and reduce genomics data. With PetaGene’s software, massive genomic data sets can be compressed without losing access or quality. And because it works with NetApp technology, storage costs can be drastically reduced.
Genomic data interpretation is made easy with Genialis, an AI-driven platform.
Regarding immunology, Immunai is using AI to make a difference. Immunai is responsible for target and treatment development using our technological platform with multi-omic patient data.
At BenevolentAI, we utilize AI to make people smarter. We build our technology so that researchers may better grasp how diseases progress, find new therapeutic targets, and make more informed decisions.
The post Top AI Tools for Genomics, Drug Discovery, And Machine Learning appeared first on MarkTechPost.