AlphaFold is an open‑source deep learning system for high‑accuracy protein structure prediction (monomers and multimers), producing ranked PDB models with per‑residue confidence (pLDDT), PAE/pTM estimates and machine‑readable outputs for downstream analysis.
ApE (A Plasmid Editor) is a lightweight, donation-supported sequence editor for designing, annotating and analyzing DNA constructs—featuring restriction maps, primer design, trace alignment, assembly wizards and rich import/export support.
Basenji is an open-source toolkit that trains deep convolutional neural networks on chromosome-scale DNA to predict quantitative regulatory activity, score variants (SAD/SED), and map distal regulatory elements and nucleotide drivers.
Benchling Molecular Biology is a cloud-based sequence design and analysis platform that helps teams design, simulate, annotate, and register DNA, RNA and protein constructs with guided cloning, primer and CRISPR tools, structure prediction, and enterprise integrations.
Bio3D is an R package for structural bioinformatics that reads and processes PDB and trajectory data to perform alignment, PCA, normal mode analysis, network and ensemble analyses, enabling comparative and dynamic studies of proteins.
Biotite is a Python library for computational molecular biology that offers NumPy-like data structures and fast, modular tools for sequence and 3D structure analysis, file I/O, database access, visualization, and external-tool integration.
Basic Local Alignment Search Tool for finding regions of local sequence similarity.
BPNet is a Python package and CLI for training base-resolution deep neural networks on functional genomics data (e.g., ChIP-nexus/ChIP-seq) and interpreting sequence motifs, their genomic locations, and motif interactions.
COBRApy is an open-source Python library for constraint-based reconstruction and analysis of metabolic networks, providing model construction, FBA/FVA, gene/reaction deletion, dFBA, sampling and solver-agnostic optimization for genome‑scale studies.
ColabFold brings state-of-the-art protein structure prediction to everyone: easy Google Colab notebooks and local tools that combine AlphaFold/RoseTTAFold with fast MMseqs2 MSA searches, batch/GPU workflows, and exports for downstream tools.
DeepChem is an open-source Python library that democratizes machine learning for chemistry, biology, materials and quantum applications by providing datasets, featurizers, models, and deployment tools to accelerate scientific ML workflows.
DeepRank converts protein–protein interfaces into 3D volumetric grids of structural and physicochemical features and provides pipelines to train CNNs for scoring, classifying, or regressing docking models; stores data in HDF5 and integrates with PyTorch.
