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

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

8 Nov 2016

Abstract excerpt

We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional...

Read the complete abstract on PubMed

Topics

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

Share to HIV/AIDS drug development and treatment
Share to HIV/AIDS Research and Interventions
Share to HIV Research and Treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 27824249
DOI: 10.1089/aid.2016.0205

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identifying Transmission Clusters with Cluster Picker and HIV-TRACEPMID 27824249Read ↗

Genetic Cluster Analysis for HIV Prevention.Semantic proximity Read ↗

Prospective Evaluation of Routine Statewide Integration of Molecular Epidemiology and Contact Tracing to Disrupt Human Immunodeficiency Virus TransmissionSemantic proximity Read ↗

Characterization of HIV-1 Transmission Clusters Inferred from the Brazilian Nationwide Genotyping Service Database.Semantic proximity Read ↗

Defining HIV-1 transmission clusters based on sequence data.Semantic proximity Read ↗

Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012-2016.Semantic proximity Read ↗

Complex patterns of Hepatitis-C virus longitudinal clustering in a high-risk population.Semantic proximity Read ↗

Phylodynamic Analysis Complements Partner Services by Identifying Acute and Unreported HIV TransmissionSemantic proximity Read ↗

Natural selection favoring more transmissible HIV detected in United States molecular transmission networkSemantic proximity Read ↗

From components to communities: bringing network science to clustering for genomic epidemiologySemantic proximity Read ↗

HIV Transmission Dynamics: Insights from Molecular Cluster Analysis of Genetic Sequence SimilaritySemantic proximity Read ↗

Automated analysis of phylogenetic clustersSemantic proximity Read ↗

Incident infection in high-priority HIV molecular transmission clusters in the United StatesSemantic proximity Read ↗

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