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H. Clifford Lane

Researcher at National Institutes of Health

Publications -  286
Citations -  41394

H. Clifford Lane is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Viral load & Medicine. The author has an hindex of 71, co-authored 254 publications receiving 35966 citations. Previous affiliations of H. Clifford Lane include Government of the United States of America & Centers for Disease Control and Prevention.

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DAVID: Database for Annotation, Visualization, and Integrated Discovery

TL;DR: DAMID is a web-accessible program that integrates functional genomic annotations with intuitive graphical summaries that assists in the interpretation of genome-scale datasets by facilitating the transition from data collection to biological meaning.
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Initiation of antiretroviral therapy in early asymptomatic HIV infection

TL;DR: The initiation of antiretroviral therapy in HIV-positive adults with a CD4+ count of more than 500 cells per cubic millimeter provided net benefits over starting such therapy in patients after the CD4+, but the risks of unscheduled hospital admissions were similar in the two groups.
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The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists

TL;DR: The DAVID Gene Functional Classification Tool uses a novel agglomeration algorithm to condense a list of genes or associated biological terms into organized classes of related genes or biology, called biological modules, for efficient interpretation of gene lists in a network context.
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Identifying biological themes within lists of genes with EASE

TL;DR: EASE is a customizable software application for rapid biological interpretation of gene lists that result from the analysis of microarray, proteomics, SAGE and other high-throughput genomic data and is robust to varying methods of normalization, intensity calculation and statistical selection of genes.
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DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists

TL;DR: The expanded DAVID Knowledgebase now integrates almost all major and well-known public bioinformatics resources centralized by the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of diverse gene/protein identifiers and annotation terms from a variety of public bio informatics databases.