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Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves a...
Parse and write protein structure files using Biopython Bio.PDB. Use for reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, extracting header information, and writing structures to variou...
MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL output files for R/Python analysis...
Metabolite identification from m/z and retention time. Covers database matching, MS/MS spectral matching, and confidence level assignment. Use when assigning compound identities to detected features in untarget...
Create reproducible bioinformatics analysis reports with R Markdown including code, results, and visualizations in HTML, PDF, or Word format.
Find cross-references between NCBI databases using Biopython Bio.Entrez. Use for navigating from genes to proteins, sequences to publications, finding related records, and discovering database relationships.
Search NCBI databases using Biopython Bio.Entrez. Use for finding records by keyword, building search queries, discovering database structure, and getting global query counts across databases.
Access and analyze AlphaFold protein structure predictions. Use when you need predicted structures for proteins without experimental structures, or confidence scores (pLDDT).
Reactome pathway enrichment using ReactomePA package. Performs over-representation analysis and GSEA on Reactome pathways, a curated peer-reviewed knowledgebase of biological pathways. Supports visualization an...
Find differentially accessible chromatin regions between conditions using DiffBind or DESeq2. Use when comparing chromatin accessibility between treatment groups, cell types, or developmental stages in ATAC-seq...
Design qPCR primers and TaqMan/molecular beacon probes using primer3-py. Configure probe Tm, primer-probe spacing, and hydrolysis probe constraints for real-time PCR assays.
KEGG pathway and module enrichment analysis using clusterProfiler enrichKEGG and enrichMKEGG. Tests whether KEGG pathways are over-represented in a gene list. Supports 4000+ organisms via KEGG online database.
Detect sample contamination and cross-species reads using FastQ Screen. Screen reads against multiple reference genomes to identify bacterial, viral, adapter, or sample swap contamination. Use when suspecting c...
End-to-end CRISPR screen analysis from FASTQ to hit genes. Orchestrates guide counting, QC, statistical analysis with MAGeCK, and hit calling with multiple methods.
Design PCR primers for a target sequence using primer3-py. Specify target regions, product size, melting temperature, and other constraints. Returns ranked primer pairs with quality metrics.
CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiment...
Create circular genome visualizations with Circos and pyCircos. Display multi-track data including ideograms, genes, variants, CNVs, and interaction arcs.
Protein grouping and inference from peptide identifications. Handles shared peptides, protein groups, and protein-level FDR control using parsimony and probabilistic approaches.
Detect contamination and assess genome quality using CheckM, CheckM2, GTDB-Tk, and GUNC for metagenome-assembled genomes and isolate assemblies.
ChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats inc...
Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use for comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matches between DN...
Access UniProt protein database for sequences, annotations, and functional information. Use when you need protein data, GO terms, domain annotations, or protein-protein interactions.
Annotate CNVs with genes, pathways, and clinical significance. Use to interpret CNV calls and identify affected genes.
Build, manage, and search spectral libraries for proteomics. Covers DDA-based library generation, predicted libraries (Prosit, DeepLC), and library formats.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。