Question 1

What are the best single-cell analysis tools listed in Awesome Computational Biology?

Accepted Answer

The list includes popular tools like Scanpy and Seurat for scRNA-seq analysis, plus newer foundation models like scGPT and Geneformer. It categorizes them under Preprocessing Tools and Single-cell Foundation Models, but doesn't rank them, so you'll need to test based on your needs.

Question 2

How do I use the APIs for accessing biological data from this list?

Accepted Answer

The API section lists endpoints like NCBI E-utilities and UniProt REST API with links to official documentation. You'll need to refer to those external sites for authentication, query examples, and rate limits, as the list doesn't provide code snippets.

Question 3

Is Awesome Computational Biology better than other bioinformatics resource lists like Awesome Bioinformatics?

Accepted Answer

Awesome Computational Biology is more focused on computational biology with deep coverage of modern ML/AI tools and datasets, whereas Awesome Bioinformatics might include broader topics. Choose based on your emphasis—this list excels in drug discovery and foundation models but may overlap with others in basic tools.

Question 4

How to contribute or update resources in the Awesome Computational Biology list?

Accepted Answer

As an open-source GitHub project, you can submit pull requests or issues on its repository to add new resources, fix links, or suggest categories. Check the README for contribution guidelines, though it doesn't detail a formal review process.

Question 5

What databases are available for protein structure prediction benchmarks?

Accepted Answer

The Benchmarks section includes datasets like ProteinGym and TAPE for evaluating protein models, and the Databases section lists resources like PDB and AlphaFold Database. These are linked but not described in depth, so you'll need to explore each for specific metrics.

Question 6

Are there any tools for molecular docking listed?

Accepted Answer

Yes, under Machine Learning Tasks and Models > Molecular Generation, tools like DiffDock and TargetDiff are listed for structure-based drug design. The list provides GitHub links but no comparisons, so review their papers for accuracy and speed.

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