Use cases · Biology
Differential expression, single-cell, structures, variants, trials and the literature behind them, worked through end to end, with every step you can open.
Real runs
Each one is a complete run in production: the question as it was asked, every step Propab took, and everything it made.
Take a public bulk RNA-seq study from GEO comparing treated and control samples in a human cell line (pick one with raw counts available), run a proper differential expression analysis with DESeq2 or an equivalent, and follow it with pathway enrichment. Deliver a volcano plot, a heatmap of the top genes, the ranked gene table and a short report that says which pathways move and how confident we should be.
End-to-end computational study of KRAS G12C. Do real computation, not mock data. Every number you report must come from code you ran. If a step fails or a tool can’t be installed, say so and use the closest working alternative. Fetch human KRAS, HRAS, NRAS and 10–15 RAS orthologs across species, align them, score per-residue conservation and build the phylogenetic tree…
Ready today
Start from one of these, or ask in your own words. Propab combines them when your question needs more than one.
Experimental and applied
Searches the literature on a target or drug and extracts in-vitro and in-vivo findings into a table, one source per row.
Experimental and applied
Maps registered trials for a disease by mechanism, phase, status and sponsor, with counts and a timeline.
Experimental and applied
Pulls Open Targets association scores and the evidence behind them for a target or disease, by evidence type.
Experimental and applied
Models how molecular profiles change over time in patients and groups patients by trajectory.
Experimental and applied
Computes power and sample size, lays out batches and fixes the multiple-testing plan before data are collected.
Experimental and applied
Predicts ADMET liabilities and docks compounds into a target pocket with a re-docking control.
Experimental and applied
Selects a minimal biomarker panel with LASSO inside cross-validation and reports held-out performance.
Experimental and applied
Kaplan–Meier curves, Cox regression and risk groups for a cohort.
Experimental and applied
Finds compounds whose LINCS L1000 signatures oppose a disease signature.
Experimental and applied
Searches and synthesises the literature on a target, disease or question, with a source for every claim.
Experimental and applied
Lists ClinicalTrials.gov records for drugs against a target, with phase, status, sponsor and NCT id.
Experimental and applied
Builds the run's report as PDF, Word or PowerPoint with publication-style figures.
Experimental and applied
Reports Open Targets tractability buckets and detects pockets on the target structure.
Experimental and applied
Proposes new indications for existing drugs from shared targets, network proximity and signature reversal.
Experimental and applied
Computes disproportionality (PRR/ROR) signals for a drug from FDA adverse-event reports.
Experimental and applied
Docks a compound library against a target, triages the hits and summarises structure–activity.
Experimental and applied
Predicts secondary-pharmacology, hERG and selectivity liabilities for compounds.
Experimental and applied
Outcomes analysis on an EHR or claims extract the researcher provides.
Experimental and applied
Simulates adaptive or enrichment designs to compare power and error rates.
Experimental and applied
Pools effect sizes across studies with random-effects models and reports heterogeneity.
Experimental and applied
Plate layouts with randomisation, edge-effect handling and covariate balance.
Bioinformatics
Finds and catalogues public datasets that fit a question across GEO, ENA/SRA, ArrayExpress, PRIDE, MetaboLights, CELLxGENE and GDC, and says which are usable.
Bioinformatics
Runs GSEA or over-representation on a gene list against MSigDB, GO and Reactome sets.
Bioinformatics
Compares tools and pipelines for a task from published benchmarks.
Bioinformatics
Aligns homologous sequences, trims the alignment and infers a maximum-likelihood tree with support values.
Bioinformatics
Finds homologues with BLAST and HMMER against Swiss-Prot and Pfam and annotates protein domains.
Single-cell
Finds the cell types that change in a disease in public single-cell data and ranks genes by that signal plus human genetic evidence.
Single-cell
Takes a count matrix through QC, normalisation, batch integration, clustering and marker-based cell-type labels.
Single-cell
Orders cells along a differentiation process, finds genes that change along it, and estimates RNA velocity where spliced/unspliced counts exist.
Single-cell
Infers ligand–receptor interactions between annotated cell types.
Single-cell
Scores each TF's regulon activity per cell and infers TF–target co-expression networks.
Single-cell
Assigns guides to cells, removes unperturbed cells and measures each knockdown's transcriptional effect.
Single-cell
QC, spatial domains and neighbourhood enrichment between cell types on Visium data.
Single-cell
Predicts single-cell responses to unseen genetic perturbations with a foundation model and scores them on held-out data.
Needs a GPU you connectSingle-cell
Chromatin-accessibility and multimodal single-cell analysis: peaks, clustering, gene activity and protein–RNA integration.
Population genetics
Tests which genes' predicted expression is associated with a trait, per tissue, from GWAS summary statistics.
Population genetics
Gives each variant at a GWAS locus a probability of being causal, with credible sets.
Population genetics
Estimates whether an exposure causally affects an outcome from two GWAS, with IVW, MR-Egger, weighted median and sensitivity checks.
Population genetics
Applies a published PGS Catalog score to genotypes and compares score distributions across populations.
Population genetics
Genotype PCA, population structure and selection statistics from population genotypes.
Genomics
Annotates a VCF with consequence, population frequency and clinical significance, and flags likely damaging variants.
Genomics
Tests genes for differential expression between conditions from a count matrix and returns fold changes, adjusted p-values and plots.
Genomics
Finds the transcription factors most likely driving an observed differential-expression signature.
Genomics
Flags loss-of-function-intolerant genes (pLI, LOEUF) in a gene list.
Genomics
Mutation and copy-number frequencies across TCGA and MSK cohorts, with mutant-versus-wild-type comparisons.
Genomics
Combines several public expression studies into one up/down disease signature by meta-analysis.
Genomics
Shows where a target is expressed across normal tissues and cell types.
Genomics
Pseudo-aligns raw RNA-seq reads to a transcriptome and produces gene counts.
Systems biology
Finds co-expressed gene modules and their hub genes and relates modules to sample traits.
Systems biology
Finds shared and layer-specific latent factors across two or more omics layers measured on the same samples.
Systems biology
Clusters samples across transcriptome, proteome and metabolome and checks cluster stability.
Systems biology
Ranks targets by multi-hop evidence paths through a biomedical knowledge graph.
Systems biology
Knocks out every gene in a genome-scale metabolic model on chosen media and reports which genes are essential and which only on one medium.
Systems biology
Loads a curated kinetic model from BioModels and runs time courses, steady states and parameter scans.
Proteomics
Tests proteins for differential abundance from a quantified mass-spec table, with FDR control.
Microbiology
Compares alpha and beta diversity and differential abundance across groups from a taxon count table.
Microbiology
Trims reads, assembles an isolate genome, predicts genes and reports assembly statistics.
Microbiology
Builds a Kraken2 index from the genomes you choose and classifies metagenomic reads against it.
Molecular biology
Designs primer pairs and TaqMan probes for a target and checks dimers, hairpins and off-target hits.
Molecular biology
Digests a sequence in silico and predicts fragment sizes and the gel.
Structural biology
Predicts a protein or complex structure with per-residue confidence.
Needs a GPU you connectStructural biology
Generates binder backbones against a target site, designs sequences and filters by predicted fold and interface.
Needs a GPU you connectStructural biology
Picks the best co-crystal structure and lists the pocket residues that contact the ligand.
Structural biology
Models ternary complexes and proposes PROTAC linkers.
Needs a GPU you connectStructural biology
Superposes an AlphaFold model onto the experimental structure and reports error by region against the model's confidence.
Structural biology
Solvates, equilibrates and simulates a protein and analyses its stability and flexibility.
Needs a GPU you connectBiochemistry
Trains and validates a model that predicts compound–target affinity from public measurements, with scaffold and cold-target splits.
Biochemistry
Pulls IC50, Ki and Kd for a drug against its target and its off-targets.
Biochemistry
Fits Michaelis–Menten and inhibition models to rate data and compares them.
Immunology
Single-cell QC scorecard for a cell-therapy product: viability, composition, activation and exhaustion states.
Immunology
Clonotypes, clonality and diversity from AIRR-formatted repertoires.
Immunology
Estimates immune-cell fractions in bulk expression samples.
Cell biology
Gates or clusters cytometry events and reports population frequencies.
Microscopy
Tiles whole-slide images and trains slide-level classifiers.
Needs a GPU you connectMicroscopy
Segments nuclei or cells in fluorescence images and measures size, shape and intensity per object.
Neuroscience
Extracts rheobase, f–I slope, resting potential, input resistance and membrane time constant from current-clamp sweeps.