7 个仓库
Deep learning models for processing and interpreting genetic data to identify variants.
Distinct from Sequence Analysis: Distinct from general sequence analysis: focuses on genomic-specific deep learning interpretation.
Explore 7 awesome GitHub repositories matching data & databases · Genomic Sequence Interpreters. Refine with filters or upvote what's useful.
This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed
Applies deep learning to process and interpret genetic data for variant identification.
This project is a scientific agent framework and workflow orchestrator designed to extend large language models with specialized tools for genomic, chemical, and biological research. It provides a system for planning research hypotheses and executing automated workflows by integrating scientific databases with dynamic code execution. The framework includes a cheminformatics modeling suite for predicting molecular bioactivity and performing virtual screening, alongside a bioinformatics analysis toolkit for processing genomic sequences and single-cell data. It also features an academic document
Analyzes DNA and protein sequences to annotate genetic variants and identify pathogenicity.
DeepChem is an open-source Python framework for applying deep learning to molecular, chemical, and biological data, serving as a comprehensive toolkit for drug discovery and materials science. At its core, it provides a featurizer-pipeline abstraction that converts raw molecular data into numerical representations, including graph-based molecular structures, SMILES tokenization vocabularies, and disk-sharded dataset persistence for handling large-scale data that exceeds RAM capacity. The framework distinguishes itself through integrated molecular docking workflows that automate pocket detecti
Featurizes genomic and proteomic sequences from alignment files for downstream machine learning models.
Biopython 是一个 Python 生物信息学库,提供用于解析、操作和分析生物序列、分子结构和系统发育树的工具。它作为基因组和蛋白质组数据的生物序列解析器,支持多种行业标准文件格式,并充当从 NCBI Entrez 仓库查询生物数据和引用的接口。 该项目以其用于蛋白质结构分析和系统发育树构建的专业工具包而著称。它包括用于处理 PDB 和 mmCIF 文件以计算分子几何结构的蛋白质结构分析器,以及用于分析物种间进化关系的系统发育树工具包。 该库涵盖了广泛的生物信息学能力,包括用于转录和翻译的基因组序列分析、序列比对管理以及群体遗传学计算。它还提供用于 3D 原子坐标操作的结构分析工具,以及用于基因组特征可视化和生物地理数据建模的实用程序。 该系统通过工具封装与外部生物信息学二进制文件集成,并支持通过 SQL 后端进行持久化生物记录存储。
Isolates non-coding DNA sequences located between genes from a larger genomic sequence.
Boltz is a deep learning molecular modeler and biomolecular structure prediction system. It uses neural network architectures to simulate the physical folding and docking of biomolecules, specifically predicting the three-dimensional shapes of protein and ligand complexes. The project functions as a protein-ligand complex predictor and binding affinity predictor, estimating the strength and probability of molecular interactions between ligands and targets. These capabilities are applied to computer aided drug design, including ligand binding affinity prediction and protein-ligand interaction
Transforms raw protein sequences into high-dimensional feature vectors using evolutionary information from related sequences.
evo2 是一个基因组大语言模型和基础模型,旨在预测、生成和分析不同物种的遗传信息。它作为一个核苷酸序列建模器和 DNA 序列生成器,使用基于 Transformer 的序列建模来处理基因组数据。 该系统提供了合成 DNA 生成功能,可根据生物学提示或物种特定标签创建新的遗传序列。它还执行核苷酸可能性预测,以对基因组变异进行评分并分析 DNA 序列中的生物学特性。 该模型通过从中间层提取高维表示来支持基因组序列分析。这些嵌入使得能够对遗传数据进行专门的分类和下游分析。
Predicts nucleotide likelihoods across a sequence to score genomic variants or analyze biological properties.
Space Station 14 is a C# multiplayer game and roleplay simulation framework. It is built upon an Entity-Component-System (ECS) game engine that separates logic into systems and data into components to manage complex entity interactions. The project functions as a grid-based physics simulator with a YAML data-driven prototype system for defining game objects. The project features a specialized 2D sprite rendering engine that maps server-side appearance data to client-side shaders. It implements a networking model with client-side prediction and dirty-flagged state synchronization to reduce inp
Allows editing base pairs within a plant's genetic sequence via a hex-style interface.