Tagged bioinformatics

Analyze TCGA cancer genomics for mutation frequencies, survival and cohorts

Compare genes across species with orthologs, paralogs and conservation data

Analyze CRISPR knockout screens with MAGeCK scores, QC and hit prioritization

Annotate DEGs and GWAS hits with gene function, pathways and disease context

Find cryo-EM maps, atomic models and micrograph datasets for a protein complex

Analyze DNA methylation, ChIP-seq, ATAC-seq and chromatin data end to end

Query ENCODE and Roadmap chromatin data for histone marks and TF binding

Find RNA-seq and microarray datasets from ArrayExpress and BioStudies

Rank CRISPR and shRNA screen hits by essentiality, druggability and clinical evidence

Score gene-disease links across DisGeNET, OpenTargets, OMIM and Orphanet

Run GO, KEGG and Reactome enrichment with ORA and GSEA on gene lists

Assess the human safety liability of knocking down or inhibiting a gene

Infer which transcription factors regulate a gene using motifs, ChIP-seq and eQTLs

Look up glycan structures, masses and glycosylation sites in GlyGen

Fine-map GWAS loci with SuSiE and FINEMAP to find causal variants and genes

Map GWAS traits to causal genes with Open Targets L2G locus-to-gene scores

Classify microbiome taxa and genome quality from MGnify and GTDB data

Find and QC microbial genome assemblies from NCBI Datasets for any organism

Compare genes across model organisms using MGI, ZFIN, FlyBase and WormBase

Characterize a disease across genomics, proteomics and pathways for biomarkers

Explore neural circuits and brain disease genetics using the Allen Brain Atlas

Run nf-core RNA-seq, variant calling and ATAC-seq pipelines on FASTQ or GEO data

Predict miRNA targets and lncRNA functions using miRBase, miRDB and LNCipedia

Trace GWAS hits through causal genes and pathways to druggable targets

Find the real protein targets of a peptide from its sequence alone

Recommend gene-informed drug dosing from CPIC guidelines and metabolizer status

Run PheWAS across UK Biobank, FinnGen and other biobanks for one variant or gene

Annotate plant genes and pathways with PlantReactome and Ensembl Plants

Compare variant frequencies across 1000 Genomes superpopulations and samples

Split patients into responder groups and risk tiers from genomic and clinical data

Run and review iterative protein binder design campaigns across model families

Map protein-protein interaction networks from STRING, BioGRID and Complex Portal

Explain how a missense variant breaks protein function using five evidence layers

Analyze phosphorylation, ubiquitination and other PTM sites with enzymes and motifs

Interpret missense variants by gained or lost ESMC sparse autoencoder features

Annotate each residue of a PDB structure for interface, pocket and burial

Predict protein 3D structures with ESMFold and fetch AlphaFold models

Retrieve protein structures from PDB, AlphaFold and SWISS-MODEL with quality checks

Design protein binders with RFdiffusion backbones and ProteinMPNN sequences

Analyze mass-spec proteomics for differential abundance, PTMs and pathways

Curate rare disease genes and assess gene-disease validity with GenCC and ClinVar

Map TF motifs, cCREs and chromatin accessibility using JASPAR and ENCODE

Explain why key protein residues matter using structure and UniProt features

Run RNA-seq differential expression with DESeq2, edgeR and limma-voom

Integrate single-cell data with scVI, scANVI, totalVI and PeakVI models

Retrieve sequences, find orthologs and run FASTQ QC and alignment

Fetch DNA, RNA and protein sequences from NCBI and ENA by accession or gene

Run single-cell RNA-seq QC and doublet detection with scanpy and anndata

Turn spatial gene expression and domain annotations into tissue-level biology