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

Nonparametric combinatorial sequence models.

Journal of computational biology : a journal of computational molecular cell biology - 1 Nov 2011

Wauthier Fabian L, Jordan Michael I, Jojic Nebojsa

Abstract excerpt

This work considers biological sequences that exhibit combinatorial structures in their composition: groups of positions of the aligned sequences are "linked" and covary as one unit across sequences. If multiple such groups exist, complex interactions can emerge between them. Sequences of this kind arise frequently in biology but methodologies for analyzing them are still being developed. This article presents a...

Read the complete abstract on PubMed

Topics

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

Share to Bayes Theorem
Share to Hemagglutinin Glycoproteins, Influenza Virus

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

Share to Histocompatibility Antigens Class I

Share to Immunoglobulins

Share to Likelihood Functions

Share to Orthomyxoviridae

Share to Sequence Analysis, Protein

Share to Statistics, Nonparametric

Source

Identifiers

PMID: 22047543
DOI: 10.1089/cmb.2011.0175

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

Nonparametric combinatorial sequence models.PMID 22047543Read ↗

Classic machine learning on top of multiple position weight matrices improves genomic prediction of transcription factor binding sitesSemantic proximity Read ↗

Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.Semantic proximity Read ↗

Models of protein sequence evolution and their applications.Semantic proximity Read ↗

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.Semantic proximity Read ↗

[From sequence variability to structural and functional prediction: modeling of homologous protein families].Semantic proximity Read ↗

Accounting for structural properties and nucleotide co-variations in the quantitative prediction of binding affinities of protein-DNA interactions.Semantic proximity Read ↗

Non-parametric Bayesian density estimation for biological sequence space with applications to pre-mRNA splicing and the karyotypic diversity of human cancerSemantic proximity Read ↗

Navigating the amino acid sequence space between functional proteins using a deep learning frameworkSemantic proximity Read ↗

Flexible model-based non-negative matrix factorization with application to mutational signatures.Semantic proximity Read ↗

Leveraging hierarchical population structure in discrete association studies.Semantic proximity Read ↗

Sequence representations and their utility for predicting protein-protein interactionsSemantic proximity Read ↗

Novel universal domain-centric method for protein classificationSemantic proximity Read ↗

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