Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

SAIVGeM: spreadsheet analysis of immunoglobulin VH gene mutations.

BioTechniques - 1 Sept 2005

Messmer Bradley T

Abstract excerpt

The analysis of mutations in immunoglobulin heavy chain variable (IGHV) region genes is a tedious process when performed by hand on multiple sequences. This report describes a set of linked Microsoft Excel files that perform several common analyses on large numbers of IGHV sequences. The spreadsheet analysis of immunoglobulin VH gene mutations (SAIVGeM) package determines the distribution of mutations among each...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to DNA Mutational Analysis
Share to Genes, Immunoglobulin

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Immunoglobulin Heavy Chains

Share to Immunoglobulin Variable Region

Share to Sequence Alignment

Share to Sequence Analysis, Protein

Share to Software

Source

Identifiers

PMID: 16206907
DOI: 10.2144/05393ST03

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

SAIVGeM: spreadsheet analysis of immunoglobulin VH gene mutations.PMID 16206907Read ↗

SAW: a graphical user interface for the analysis of immunoglobulin variable domain sequences.Semantic proximity Read ↗

Comparative analysis of human and mouse immunoglobulin variable heavy regions from IMGT/LIGM-DB with IMGT/HighV-QUEST.Semantic proximity Read ↗

IgBLAST: an immunoglobulin variable domain sequence analysis toolSemantic proximity Read ↗

SoDA2: a Hidden Markov Model approach for identification of immunoglobulin rearrangementsSemantic proximity Read ↗

Many human immunoglobulin heavy-chain IGHV gene polymorphisms have been reported in error.Semantic proximity Read ↗

IMGT/DomainGapAlign: the IMGT® tool for the analysis of IG, TR, MH, IgSF, and MhSF domain amino acid polymorphism.Semantic proximity Read ↗

iHMMune-align: hidden Markov model-based alignment and identification of germline genes in rearranged immunoglobulin gene sequencesSemantic proximity Read ↗

Deep learning model of somatic hypermutation reveals importance of sequence context beyond hotspot targetingSemantic proximity Read ↗

Gene-Specific Substitution Profiles Describe the Types and Frequencies of Amino Acid Changes during Antibody Somatic HypermutationSemantic proximity Read ↗

Inter- and intraspecies comparison of phylogenetic fingerprints and sequence diversity of immunoglobulin variable genes.Semantic proximity Read ↗

Deep learning model of somatic hypermutation reveals importance of sequence context beyond targeting of AID and Polη hotspotsSemantic proximity Read ↗

Use of IGHJ and IGHD gene mutations in analysis of immunoglobulin sequences for the prognosis of chronic lymphocytic leukemia.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.