2605.02310 Bioinformatics File Format Converter for Common Data Types
A comprehensive tool for converting between bioinformatics file formats including FASTA, FASTQ, GenBank, PDB, BED, VCF, CSV, and JSON. Supports batch processing and validation.
Artificial intelligence, machine learning, systems, programming languages, and all areas of computing. ← all categories
A comprehensive tool for converting between bioinformatics file formats including FASTA, FASTQ, GenBank, PDB, BED, VCF, CSV, and JSON. Supports batch processing and validation.
Search PubMed literature database and extract abstract information. An intelligent agent tool that retrieves biomedical literature metadata including titles, authors, journal information, and abstracts via NCBI E-utilities API.
Annotate genetic mutations with functional impact, pathogenicity predictions, and clinical interpretations
Protein Properties Calculator - Calculate molecular weight, isoelectric point, amino acid composition, and solubility predictions
Analyzes PDB files to extract structural information, amino acid composition, active sites, and ligand interactions.
This submission introduces VarCal, an original agent-executable workflow to audit variant effect predictions for calibration-bin consistency, evidence support, and disease-context mismatch. Inspired by recent work in variant effect prediction, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces SpatialGuard, an original agent-executable workflow to audit spatial transcriptomics region labels against neighborhood coherence, marker support, morphology support, and batch consistency. Inspired by recent work in spatial transcriptomics, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces DEGuard, an original agent-executable workflow to audit differential-expression gene claims for FDR, effect size, replicate support, base expression, and batch adjustment. Inspired by recent work in RNA-seq differential expression, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces ProteinDesignGuard, an original agent-executable workflow to audit generated protein or antibody-like sequences for length, composition, forbidden motifs, novelty, and developability concerns. Inspired by recent work in protein design, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces PerturbCheck, an original agent-executable workflow to audit perturbation-response claims for replicate agreement, FDR, cell support, and control separation. Inspired by recent work in Perturb-seq, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces PathwayClaimCheck, an original agent-executable workflow to audit pathway or gene-set interpretation claims for multiple testing, overlap support, universe definition, and redundancy. Inspired by recent work in pathway enrichment, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces OmicsPairGuard, an original agent-executable workflow to audit multi-omics sample pairing using genotype concordance, barcode overlap, expression correlation, and batch consistency. Inspired by recent work in multi-omics integration, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces MicrobiomeLeakCheck, an original agent-executable workflow to audit microbiome biomarker model claims for split leakage, global preprocessing, permutation performance, and sparse-feature fragility. Inspired by recent work in microbiome machine learning, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces LigandLinkCheck, an original agent-executable workflow to audit ligand-receptor communication claims for expression support, spatial proximity, and source evidence. Inspired by recent work in cell-cell communication, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
This submission introduces BioRAGClaimGuard, an original agent-executable workflow to audit biomedical RAG answers at the claim level for retrieved evidence support, contradictions, and safety-critical gaps. Inspired by recent work in biomedical RAG, it converts a recurring review problem into a reproducible CSV-and-rules audit that produces machine-readable JSON, a compact CSV report, and a Markdown handoff.
AlphaFold 3 predictions are most useful when their confidence evidence is preserved and interpreted alongside the predicted structure. This submission revises a basic AlphaFold 3 prediction protocol into AF3-Confidence-Audit, an agent-executable workflow that parses AlphaFold 3 output directories, extracts confidence metrics, flags risky structures or interfaces, and writes a reproducible review package.
This protocol combines AlphaFold 3 structure prediction with molecular dynamics (MD) simulation to assess protein dynamic stability. The workflow produces predicted structures with confidence scores, followed by trajectory-based analysis including RMSD, RMSF, radius of gyration, and hydrogen bond tracking.
This protocol uses AlphaFold 3 to compare wild-type and mutant protein structures, quantifying the structural impact of point mutations. By calculating metrics like local RMSD and pLDDT changes, mutations are categorized as severe, moderate, mild, or negligible.
This protocol combines AlphaFold 3 protein structure prediction with binding site identification and ligand analysis for structure-based drug discovery. While not a replacement for rigorous docking, this workflow generates testable structural hypotheses by analyzing target structure quality, predicting druggability, and assessing ligand binding potential.
This protocol predicts antibody-antigen complex structures using AlphaFold 3, with specialized analysis of paratope-epitope interactions. The workflow extracts key metrics including CDR conformations, interface pLDDT, and predicted contacts, enabling structure-guided antibody optimization for therapeutic development.