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

Statistical geometry approach to the study of functional effects of human nonsynonymous SNPs.

Human mutation - 1 Nov 2005

Barenboim Maxim, Jamison D Curtis, Vaisman Iosif I

Abstract excerpt

The ability to predict the effect of nonsynonymous SNPs (nsSNPs) on protein function is important for the success of genetic disease association studies. Here we present a statistical geometry approach to nsSNP classification based on Delaunay tessellation, whereby the impact of nsSNPs on protein function is correlated with the change in the four-body statistical potential (DeltaQ) of the protein caused by the...

Read the complete abstract on PubMed

Topics

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

Share to Amino Acid Substitution
Share to Computational Biology
Share to Data Interpretation, Statistical

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

Share to Genetic Predisposition to Disease

Share to Mathematical Computing

Share to Polymorphism, Single Nucleotide

Share to Protein Conformation

Share to Proteins

Source

Identifiers

PMID: 16200641
DOI: 10.1002/humu.20238

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

Statistical geometry approach to the study of functional effects of human nonsynonymous SNPs.PMID 16200641Read ↗

Structural location of disease-associated single-nucleotide polymorphisms.Semantic proximity Read ↗

topoSNP: a topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association.Semantic proximity Read ↗

Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers.Semantic proximity Read ↗

Predicting the transactivation activity of p53 missense mutants using a four-body potential score derived from Delaunay tessellations.Semantic proximity Read ↗

Human non-synonymous SNPs: server and survey.Semantic proximity Read ↗

Assessing Protein Surface-Based Scoring for Interpreting Genomic VariantsSemantic proximity Read ↗

Assessing Protein Surface-Based Scoring for Interpreting Genomic Variants.Semantic proximity Read ↗

Modeling and analyzing three-dimensional structures of human disease proteins.Semantic proximity Read ↗

Computational SNP analysis: current approaches and future prospects.Semantic proximity Read ↗

An Association Test of the Spatial Distribution of Rare Missense Variants within Protein Structures Improves Statistical Power of Sequencing StudiesSemantic proximity Read ↗

Combination use of protein-protein interaction network topological features improves the predictive scores of deleterious non-synonymous single-nucleotide polymorphisms.Semantic proximity Read ↗

CASTp: computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues.Semantic proximity Read ↗

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