Biology & Genomics

Filter designed proteins by pLDDT, ipTM, PAE and sequence liability checks

Design protein sequences for RFdiffusion backbones with ProteinMPNN

Program liquid handlers, plate readers and pumps in Python with PyLabRobot

Run LC-MS/MS proteomics and metabolomics workflows in Python with OpenMS

Generate de novo protein backbones and binder scaffolds with RFdiffusion

Run single-cell RNA-seq QC, clustering, UMAP and marker gene analysis with Scanpy

Run a local Scanpy pipeline for single-cell QC, clustering and marker discovery

Model single-cell omics with scvi-tools for batch correction and differential expression

Run FastQC, BWA and SAMtools pipelines from raw reads to processed BAM files

Annotate single-cell types with SCSA, CellMatch and KNN transfer in omicverse

Infer cell-cell ligand-receptor networks from annotated single-cell data with CellPhoneDB

Cluster single-cell data and correct batch effects with omicverse workflows

Follow omicverse checklists for AUCell scoring and metacell differential expression

Integrate single-cell multi-omics data with MOFA, GLUE, SIMBA and TOSICA

QC, normalize and embed single-cell counts with omicverse preprocessing workflows

Reproduce single-cell trajectory analyses with PAGA, Palantir, VIA and velocity

Map single-cell atlases onto spatial transcriptomics slides with Single2Spatial

Design soluble proteins with SolubleMPNN to reduce aggregation and raise E. coli yield

Preprocess and deconvolve Visium and Stereo-seq spatial transcriptomics with omicverse

Query STRING for protein interactions and draw network figures for gene lists

Predict protein structures with AlphaFold, Boltz or Chai and compare RMSD locally

Ingest TCGA expression, sample sheets and clinical data into AnnData with omicverse

Humanize and optimize therapeutic antibodies for developability and immunogenicity

Find small molecule binders for a protein target with docking and ADMET profiles

Retrieve compound identifiers, properties and bioactivity from PubChem and ChEMBL

Predict chemical toxicity for AMES, DILI and LD50 with safety label data

Analyze pooled CRISPR screens with MAGeCK and BAGEL to find essential genes

Find existing drugs to repurpose for new indications using targets and safety data

Validate drug targets on druggability, safety, clinical precedent and evidence

Analyze methylation arrays, ChIP-seq peaks and ATAC-seq chromatin accessibility

Find gene expression datasets in ArrayExpress and BioStudies with sample metadata

Run GO, KEGG and Reactome gene set enrichment with gseapy and STRING

Fine-map GWAS loci to rank causal variants and link them to candidate genes

Interpret GWAS variants with GWAS Catalog, Open Targets Genetics and ClinVar evidence

Find genes linked to a disease or trait using GWAS Catalog and locus-to-gene scores

Analyze T-cell and B-cell receptor repertoires for clonality, diversity and V(D)J usage

Identify metabolites and search HMDB, MetaboLights and Metabolomics Workbench

Normalize and analyze LC-MS, GC-MS and NMR metabolomics data with pathway enrichment

Integrate transcriptomic, proteomic and metabolomic data with MOFA and NMF clustering

Build compound-target-disease networks for drug repurposing and polypharmacology

Compute treeness, parsimony sites and alignment statistics for phylogenetic trees

Retrieve protein structures from RCSB PDB, PDBe and AlphaFold with quality notes

Design protein binders and enzymes with RFdiffusion, ProteinMPNN and AlphaFold checks

Analyze MaxQuant, DIA-NN and Spectronaut proteomics outputs for differential expression

Run DESeq2 differential expression on bulk RNA-seq with PyDESeq2 and LFC shrinkage

Retrieve DNA, RNA and protein sequences from NCBI and ENA with accession lookups

Cluster expression matrices and annotate cell types with scanpy and scipy

Analyze spatially variable genes and domains across Visium, MERFISH and Slide-seq

Map gene expression in tissue with spatial clustering and cell proximity analysis