软件包材料与化学科研包与框架

cobrapy

COBRApy

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

这页展示的是上游仓库条目，不代表已进入 SCI Skills 精选目录。

原始路径: scientific-skills/cobrapy
允许工具: -
仓库版本: 2.31.0
同步时间: 2026年3月27日

条目说明

COBRApy is a Python library for constraint-based reconstruction and analysis (COBRA) of metabolic models, essential for systems biology research. Work with genome-scale metabolic models, perform computational simulations of cellular metabolism, conduct metabolic engineering analyses, and predict phenotypic behaviors.

adaptyv

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

软件包机器学习

aeon

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

软件包生信与基因组

anndata

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.