Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Derrick E. Wood"'
Autor:
Laurel A. Keefer, James R. White, Derrick E. Wood, Kelly M. R. Gerding, Kenneth C. Valkenburg, David Riley, Christopher Gault, Eniko Papp, Christine M. Vollmer, Amy Greer, James Hernandez, Paul M. McGregor, Adriana Zingone, Bríd M. Ryan, Kristen Deak, Shannon J. McCall, Michael B. Datto, James L. Prescott, John F. Thompson, Gustavo C. Cerqueira, Siân Jones, John K. Simmons, Abigail McElhinny, Jennifer Dickey, Samuel V. Angiuoli, Luis A. Diaz, Victor E. Velculescu, Mark Sausen
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-15 (2022)
The genomic profiling of tumours has not been widely adopted in the clinic due to technical and practical hurdles. Here, the authors develop PGDx elio tissue complete, a scalable, standardised and FDA-cleared test comprising a targeted gene panel and
Externí odkaz:
https://doaj.org/article/e4aa27119f0a4f1f9ac75c8283f59ea8
Autor:
Steven L. Salzberg, Derrick E. Wood
Publikováno v:
Frontiers in Bioinformatics, Vol 1 (2021)
Ten years ago, the dramatic rise in the number of microbial genomes led to an inflection point, when the approach of finding short, exact matches in a comprehensive database became just as accurate as older, slower approaches. The new idea led to a m
Externí odkaz:
https://doaj.org/article/e6200e23191f450db669fbbddf965e8c
Publikováno v:
Genome Biology, Vol 20, Iss 1, Pp 1-13 (2019)
Abstract Although Kraken’s k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by
Externí odkaz:
https://doaj.org/article/01cfbfa980fd45e5bd752c20bb115e08
Publikováno v:
PeerJ, Vol 2, p e675 (2014)
The raw data from a genome sequencing project sometimes contains DNA from contaminating organisms, which may be introduced during sample collection or sequence preparation. In some instances, these contaminants remain in the sequence even after assem
Externí odkaz:
https://doaj.org/article/de3fa92d5ead4caa8db2598b90c69178
Autor:
Jennifer Lu, Natalia Rincon, Derrick E. Wood, Florian P. Breitwieser, Christopher Pockrandt, Ben Langmead, Steven L. Salzberg, Martin Steinegger
Publikováno v:
Nat Protoc
Metagenomic experiments expose the wide range of microscopic organisms in any microbial environment through high-throughput DNA sequencing. The computational analysis of the sequencing data is critical for the accurate and complete characterization o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e98deafaec38f29c17bf5fbfcc48ca04
https://pubmed.ncbi.nlm.nih.gov/36171387
https://pubmed.ncbi.nlm.nih.gov/36171387
Autor:
Laurel A. Keefer, James R. White, Derrick E. Wood, Kelly M. R. Gerding, Kenneth C. Valkenburg, David Riley, Christopher Gault, Eniko Papp, Christine M. Vollmer, Amy Greer, James Hernandez, Paul M. McGregor, Adriana Zingone, Bríd M. Ryan, Kristen Deak, Shannon J. McCall, Michael B. Datto, James L. Prescott, John F. Thompson, Gustavo C. Cerqueira, Siân Jones, John K. Simmons, Abigail McElhinny, Jennifer Dickey, Samuel V. Angiuoli, Luis A. Diaz, Victor E. Velculescu, Mark Sausen
Publikováno v:
Nature communications. 13(1)
The lack of validated, distributed comprehensive genomic profiling assays for patients with cancer inhibits access to precision oncology treatment. To address this, we describe elio tissue complete, which has been FDA-cleared for examination of 505 c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::559b64c8ec773a2141e7483647eba30e
https://pubmed.ncbi.nlm.nih.gov/35595835
https://pubmed.ncbi.nlm.nih.gov/35595835
Autor:
Noushin Niknafs, Valsamo Anagnostou, Rachel Karchin, Sonya Parpart-Li, Derrick E. Wood, Peter R. LoVerso, Beth O. Van Emburgh, Jason Mitchell, Andrew Georgiadis, Victor E. Velculescu, Christine McCord, David R. Riley, Luis A. Diaz, Siân Jones, Samuel V. Angiuoli, James R. White, Mark Sausen, Eniko Papp
Publikováno v:
Science Translational Medicine. 10
Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a983f8ed5b7f7bf8337e3e9b5ca4907
https://doi.org/10.1126/scitranslmed.aar7939
https://doi.org/10.1126/scitranslmed.aar7939
Publikováno v:
Evolutionary Bioinformatics
Evolutionary Bioinformatics, Vol 9 (2013)
Evolutionary Bioinformatics, Vol 2013, Iss 9, Pp 127-136 (2013)
Evolutionary Bioinformatics, Vol 9 (2013)
Evolutionary Bioinformatics, Vol 2013, Iss 9, Pp 127-136 (2013)
Background The expression levels of bacterial genes can be measured directly using next-generation sequencing (NGS) methods, offering much greater sensitivity and accuracy than earlier, microarray-based methods. Most bioinformatics software for estim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6d82fdc387702704da1fe962236ea5d
http://europepmc.org/articles/PMC3603529
http://europepmc.org/articles/PMC3603529
Autor:
Derek Murphy, Sian Jones, Mark Sausen, Sonya Parpart-Li, Samuel A. Angiuoli, Andrew Georgiadis, Naomi Sengamalay, Marian Novak, Derrick E. Wood, David R. Riley
Publikováno v:
Cancer Research. 78:1286-1286
Failure of the DNA mismatch repair (MMR) pathway during DNA replication in cancer leads to the increased accumulation of somatic mutations. The molecular hallmark of MMR deficiency is microsatellite instability (MSI), which presents as polymorphism o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89b5f49b0b4c873000bbf3f235581f25
https://doi.org/10.1158/1538-7445.am2018-1286
https://doi.org/10.1158/1538-7445.am2018-1286
Autor:
Christine McCord, James R. White, Derrick E. Wood, Sonya Parpart-Li, Noushin Niknafs, Luis A. Diaz, Rachel Karchin, Andrew Georgiadis, Eniko Papp, Samuel V. Angiuoli, Sian Jones, Victor E. Velculescu, David R. Riley, Jason S. Mitchell, Peter R. LoVerso, Beth O. Van Emburgh, Mark Sausen, Valsamo Anagnostou
Publikováno v:
Cancer Research. 78:3271-3271
Variability in the accuracy for somatic mutation detection may affect discovery of alterations and therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery method based on machine learning approaches
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a363c280ab2b0d1b37d7116f6f27975
https://doi.org/10.1158/1538-7445.am2018-3271
https://doi.org/10.1158/1538-7445.am2018-3271