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Richa Agarwala

Researcher at National Institutes of Health

Publications -  78
Citations -  42117

Richa Agarwala is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Genome & Human genome. The author has an hindex of 43, co-authored 76 publications receiving 38969 citations. Previous affiliations of Richa Agarwala include United States Department of Health and Human Services.

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Journal ArticleDOI

Initial sequencing and analysis of the human genome.

Eric S. Lander, +248 more
- 15 Feb 2001 - 
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
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Initial sequencing and comparative analysis of the mouse genome.

Robert H. Waterston, +222 more
- 05 Dec 2002 - 
TL;DR: The results of an international collaboration to produce a high-quality draft sequence of the mouse genome are reported and an initial comparative analysis of the Mouse and human genomes is presented, describing some of the insights that can be gleaned from the two sequences.
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Insights into social insects from the genome of the honeybee Apis mellifera

George M. Weinstock, +228 more
- 26 Oct 2006 - 
TL;DR: The genome sequence of the honeybee Apis mellifera is reported, suggesting a novel African origin for the species A. melliferA and insights into whether Africanized bees spread throughout the New World via hybridization or displacement.
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Mapping copy number variation by population-scale genome sequencing

Ryan E. Mills, +374 more
- 03 Feb 2011 - 
TL;DR: A map of unbalanced SVs is constructed based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations, and serves as a resource for sequencing-based association studies.
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Protein database searches using compositionally adjusted substitution matrices

TL;DR: This work has recently developed a general procedure for transforming a standard matrix into one appropriate for the comparison of two sequences with arbitrary, and possibly differing compositions.