BioMate takes any research question in plain English — from RNA-seq differential expression to bispecific antibody format selection — routes it to the right tool, runs it on cloud compute, and returns a ranked result with a full citable methods section. No code, no pipeline configuration.
The videos below are a sample from a library of 2,000+ workflows spanning transcriptomics, genomics, epigenomics, structural biology, drug design, clinical modeling, and more. Each one shows how a single sentence becomes a publication-ready result.
BioMate — The AI Lab Platform for Life Sciences
An overview of BioMate — the AI-native lab platform that turns complex bioinformatics pipelines into a conversation. From raw data to publication-ready outputs, without writing code.
Multi-step Workflow Automation with Quality Control
BioMate runs a CryoSPARC single-particle analysis end to end — 5 phases, 23 steps, live QC gates, auto-loop remediation, and per-step output previews, all launched from a single chat message.
After Run Report — Reproducibility in One Click
Every completed BioMate run generates a structured 7-tab report: Findings, Outputs, Methods, Parameters, Software, Citations, and QC Audit. Download as DOCX, Markdown, or LaTeX — manuscript-ready without copy-paste.
IND Report — Automated Section 2.6 Nonclinical Dossier with 21 CFR Part 11 Sign-Off
A five-step pipeline — ADMET profiling, PBPK modeling, lead prioritization, and LLM-generated regulatory prose — builds an IND-quality section 2.6 dossier. The live document panel updates in place as each step completes, with full 21 CFR Part 11 sign-and-freeze.
Omics pipelines — bulk RNA-seq, single-cell, and DNA methylation — routed automatically from plain English to DESeq2, Seurat, minfi, and more. No R environment setup, no pipeline configuration.
Bulk RNA-seq: DESeq2 + GO Enrichment, No R Code
Describe your bulk RNA-seq experiment in plain English — BioMate selects DESeq2, runs GO enrichment via clusterProfiler, and returns 2,841 ranked differentially expressed genes with a citable methods section. No R environment, no pipeline configuration.
Bioconductor methods in BioMate → · Why AI writes Bioconductor code that doesn't run →
Single-Cell RNA-seq: 8 Cell Types Resolved, No Code
Describe your single-cell experiment in plain English — BioMate routes to Seurat + SingleR, resolves 8 cell types, and delivers a UMAP with condition-level abundance results ready for publication.
DNA Methylation: 847 DMRs + Pathway Enrichment, No Code
From bisulfite sequencing inputs to 847 differentially methylated regions with pathway enrichment — BioMate runs the full minfi + DMRcate pipeline and returns a citable methods section. No R setup required.
Therapeutic format and modality decisions — bispecific antibodies, CAR-T, base editing, GLP-1, and BCMA myeloma triage — scored, ranked, and cross-referenced to clinical precedent.
Bispecific Antibody Design: AI Picks ivonescimab Format Over CrossMab
Ask for any bispecific format — BioMate scores all five common architectures across six mechanistic axes and ranks them, catching that the tetravalent cooperative format outperforms CrossMab on cooperative avidity before you run a single binding assay.
CAR-T Design: CD19 CAR + LNP, Fratricide Check, Full Construct
Specify a target and delivery modality — BioMate selects the LNP vector, runs a fratricide check, and assembles a full CAR construct with clinical precedent. From one sentence to a 1,485-aa sequence.
Base Editing: PCSK9 Knockout Design Matches VERVE-102 in Seconds
One sentence about your target — BioMate identifies the optimal base-editing site, selects the right editor class, designs a guide RNA, and cross-references clinical precedent, matching VERVE-102's approach to PCSK9 from scratch.
GLP-1 for MASH: AI Picks Peptide Over 4 Modalities in Seconds
Name your target and indication — BioMate runs a structured bake-off across all relevant modalities, scores them on pharmacology and clinical evidence, and ranks subcutaneous peptide injection #1 for MASH. The field's decade-long conclusion, in seconds.
GLP-1 modality bakeoff — why "the next GLP-1" is an indication question →
BCMA Myeloma: CAR-T vs BiTE vs ADC — AI Ranks All 4 Modalities
Give BioMate a target and tumor type — it maps every viable modality class, scores them against clinical evidence from ide-cel, cilta-cel, and teclistamab, and returns a ranked recommendation with competitive landscape.
Recovering 7-of-7 Q4 2024 FDA approvals from first principles →