Results for “protein”

13 skills
More results
lingxling
gget
Queries 20+ bioinformatics databases from the command line or Python for gene info, sequences, BLAST/BLAT, protein structures, viral data, and expression metrics.
253 · bundle
k-dense-ai
gget
Query 20+ bioinformatics databases from the command line or Python for gene information, sequences, protein structures, enrichment analysis, and more.
30.2k · bundle
k-dense-ai
pyopenms
Analyze proteomics and metabolomics mass spectrometry data with PyOpenMS: read/write MS file formats, process spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines using ready-to-run scripts.
30.2k · bundle
lingxling
matchms
Process and analyze mass spectrometry data with the Matchms Python library, including importing spectra, filtering peaks, calculating similarity scores, and building reproducible analytical workflows.
253 · bundle
k-dense-ai
deepchem
Predict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.
30.2k · bundle
gabrielmoreira
proteomics-de
Performs differential expression analysis on label-free quantitative (LFQ) proteomics data from MaxQuant and DIA-NN outputs, including preprocessing, imputation, statistical testing, and visualization.
17 · bundle
lucaspmarie-a11y
biopython
Provides reference documentation and code patterns for Biopython, covering sequence handling, alignments, NCBI database access, BLAST, protein structures, phylogenetics, and other bioinformatics tasks.
5
k-dense-ai
scikit-bio
Analyze biological sequences, alignments, phylogenetic trees, and diversity metrics (alpha/beta, UniFrac) with ordination (PCoA) and PERMANOVA for microbiome and community ecology data.
30.2k · bundle
alterlab-ieu
alterlab-cbioportal
Query cBioPortal via its keyless REST API for cancer genomics across TCGA, GENIE, MSK-IMPACT and hundreds of studies — somatic mutations, copy-number alterations (GISTIC), mRNA/protein expression, structural variants, and patient-level clinical/survival data. Use when asked how often a gene is mutated/amplified/deleted in a tumor type, to profile oncogenes or tumor suppressors across cancers (pan-cancer alteration frequency), to pull patient-level mutations joined to OS/clinical outcomes, or to validate a cancer target from cohort genomics. For germline variant pathogenicity use alterlab-clinvar; for mutational-signature (SBS) decomposition use alterlab-cosmic; for CRISPR/RNAi gene-dependency use alterlab-depmap; for aggregated target-disease evidence use alterlab-opentargets. Part of the AlterLab Academic Skills suite.
60 · bundle