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Bioinformatics

Genomics and biological data.

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bioinformatics
471

bio-workflows-gwas-pipeline

End-to-end GWAS workflow from VCF to association results. Covers PLINK QC, population structure correction, and association testing for case-control or quantitative traits. Use when running genome-wide association studies.

GPTomics
GPTomics
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open
bioinformatics
471

bio-metabolomics-xcms-preprocessing

XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for untargeted metabolomics.

GPTomics
GPTomics
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open
bioinformatics
471

bio-epitranscriptomics-m6a-differential

Identify differential m6A methylation between conditions from MeRIP-seq. Use when comparing epitranscriptomic changes between treatment groups or cell states.

GPTomics
GPTomics
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open
bioinformatics
471

bio-alignment-io

Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.

GPTomics
GPTomics
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open
bioinformatics
471

bio-microbiome-taxonomy-assignment

Taxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and exact matching approaches. Use when assigning taxonomy to ASVs after DADA2 amplicon processing.

GPTomics
GPTomics
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bioinformatics
471

bio-workflows-microbiome-pipeline

End-to-end 16S amplicon workflow from FASTQ reads to differential abundance. Orchestrates DADA2 ASV inference, taxonomy assignment, diversity analysis, and compositional testing with ALDEx2. Use when processing 16S/ITS amplicon data.

GPTomics
GPTomics
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bioinformatics
471

bio-longread-medaka

Polish assemblies and call variants from Oxford Nanopore data using medaka. Uses neural networks trained on specific basecaller versions. Use when improving ONT-only assemblies or calling variants from Nanopore data without short-read polishing.

GPTomics
GPTomics
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open
bioinformatics
471

bio-proteomics-quantification

Protein quantification from mass spectrometry data including label-free (LFQ, intensity-based), isobaric labeling (TMT, iTRAQ), and metabolic labeling (SILAC) approaches. Use when extracting protein abundances from MS data for differential analysis.

GPTomics
GPTomics
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open
bioinformatics
471

bio-crispr-screens-batch-correction

Batch effect correction for CRISPR screens. Covers normalization across batches, technical replicate handling, and batch-aware analysis. Use when combining screens from multiple batches or correcting systematic technical variation.

GPTomics
GPTomics
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open
bioinformatics
471

bio-methylation-bismark-alignment

Bisulfite sequencing read alignment using Bismark with bowtie2/hisat2. Handles genome preparation and produces BAM files with methylation information. Use when aligning WGBS, RRBS, or other bisulfite-converted sequencing reads to a reference genome.

GPTomics
GPTomics
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open
bioinformatics
471

bio-workflows-metabolomics-pipeline

End-to-end metabolomics workflow from raw MS data to pathway analysis. Orchestrates XCMS preprocessing, annotation, normalization, statistical analysis, and pathway mapping. Use when processing LC-MS metabolomics data.

GPTomics
GPTomics
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open
bioinformatics
471

bio-workflows-metagenomics-pipeline

End-to-end metagenomics workflow from FASTQ to taxonomic and functional profiles. Covers Kraken2 classification, Bracken abundance estimation, and HUMAnN functional profiling. Use when profiling metagenomic samples.

GPTomics
GPTomics
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open
bioinformatics
471

bio-genome-intervals-bigwig-tracks

Create and read bigWig browser tracks for visualizing continuous genomic data. Convert bedGraph to bigWig, extract signal values, and generate coverage tracks using UCSC tools and pyBigWig. Use when preparing coverage tracks for genome browsers or extracting signal at specific regions.

GPTomics
GPTomics
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bioinformatics
471

bio-genome-assembly-short-read-assembly

De novo genome assembly from Illumina short reads using SPAdes. Covers bacterial, fungal, and small eukaryotic genome assembly, as well as metagenome and transcriptome assembly modes. Use when assembling genomes from Illumina reads.

GPTomics
GPTomics
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bioinformatics
471

bio-genome-engineering-grna-design

Design guide RNAs for CRISPR-Cas9/Cas12a experiments using CRISPRscan and local scoring algorithms. Score guides for on-target activity using Rule Set 2 and Azimuth models. Use when designing sgRNAs for gene knockout, activation, or repression experiments.

GPTomics
GPTomics
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bioinformatics
471

bio-genome-assembly-assembly-polishing

Polish genome assemblies to reduce errors using short reads (Pilon), long reads (Racon), or ONT-specific tools (medaka). Essential for improving long-read assembly accuracy. Use when improving assembly accuracy with polishing tools.

GPTomics
GPTomics
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bioinformatics
471

bio-genome-assembly-assembly-qc

Assess genome assembly quality using QUAST for contiguity metrics and BUSCO for completeness. Essential for evaluating assembly success and comparing assemblers. Use when evaluating assembly completeness and quality.

GPTomics
GPTomics
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open
bioinformatics
471

bio-reverse-complement

Generate reverse complements and complements of DNA/RNA sequences using Biopython. Use when working with opposite strands, primer design, or converting between template and coding strands.

GPTomics
GPTomics
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open
bioinformatics
471

bio-genome-assembly-metagenome-assembly

Metagenome assembly from long reads using metaFlye and metaSPAdes with binning strategies. Use when reconstructing genomes from microbial communities, recovering metagenome-assembled genomes (MAGs), or resolving strain-level variation in complex samples.

GPTomics
GPTomics
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bioinformatics
471

bio-epidemiological-genomics-amr-surveillance

Detect and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns. Use when screening genomes for AMR genes or tracking resistance in surveillance programs.

GPTomics
GPTomics
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bioinformatics
471

bio-gene-regulatory-networks-differential-networks

Compare gene regulatory and co-expression networks between biological conditions to identify rewired regulatory relationships using DiffCorr. Detects gained, lost, and reversed gene-gene correlations between conditions. Use when comparing co-expression networks between disease vs control, treatment conditions, or developmental stages.

GPTomics
GPTomics
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bioinformatics
471

bio-epidemiological-genomics-variant-surveillance

Assign pathogen lineages and track variants using Nextclade and pangolin for viral surveillance. Monitor variant prevalence and identify emerging variants of concern. Use when classifying viral sequences, tracking lineage dynamics, or monitoring for variants of concern.

GPTomics
GPTomics
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bioinformatics
471

bio-gene-regulatory-networks-coexpression-networks

Build weighted gene co-expression networks to identify modules of co-regulated genes and relate them to phenotypes using WGCNA and CEMiTool. Detects hub genes and module-trait relationships from bulk or single-cell expression data. Use when finding co-expression modules, identifying hub genes, or relating gene networks to clinical or experimental variables.

GPTomics
GPTomics
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bioinformatics
471

bio-flow-cytometry-differential-analysis

Differential abundance and state analysis for cytometry data. Compare cell populations between conditions using statistical methods. Use when testing for significant changes in cell frequencies or marker expression between groups.

GPTomics
GPTomics
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