Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Ari Frank"'
Autor:
Díaz Correa, Ari Frank
Publikováno v:
Repositorio Institucional-UCV
Universidad César Vallejo
UCV-Institucional
Universidad Cesar Vallejo
instacron:UCV
Universidad César Vallejo
UCV-Institucional
Universidad Cesar Vallejo
instacron:UCV
La presente investigación tuvo como objetivo general establecer de qué manera la justicia organizacional se relaciona con la conducta ciudadana organizativa en los colaboradores de la SUTRAN – Lima durante el 2021, y se planteó como hipótesis g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::914bbbf1d0ea6f6b948d66c6bd808ef7
Autor:
Richard D. Smith, Gordon A. Anderson, Nuno Bandeira, Ronald J. Moore, Pavel A. Pevzner, Jeremy Carver, Matthew E. Monroe, Ari Frank, Anuj R. Shah
Publikováno v:
Nature methods
Tandem mass spectrometry (MS/MS) experiments yield multiple, nearly identical spectra of the same peptide in various laboratories, but proteomics researchers typically do not leverage the unidentified spectra produced in other labs to decode spectra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7663678a9b8b9b7ac34f529bf5b98c4
https://doi.org/10.1038/nmeth.1609
https://doi.org/10.1038/nmeth.1609
Publikováno v:
Analytical Chemistry. 80:2499-2505
Recent advances in mass spectrometry instrumentation, such as FTICR and OrbiTrap, have made it possible to generate high-resolution spectra of entire proteins. While these methods offer new opportunities for performing "top-down" studies of proteins,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf8304991b59e71e0123f436478a9da2
https://doi.org/10.1021/ac702324u
https://doi.org/10.1021/ac702324u
Autor:
Shamil R. Sunyaev, Ari Frank, Vineeth Surendranath, Andandrej Shevchenko, Henrik Thomas, Patrice Waridel, Pavel A. Pevzner
Publikováno v:
PROTEOMICS. 7:2318-2329
LC-MS/MS analysis on a linear ion trap LTQ mass spectrometer, combined with data processing, stringent, and sequence-similarity database searching tools, was employed in a layered manner to identify proteins in organisms with unsequenced genomes. Hig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7090ade95ad3c91a61d06bdbbcdc7020
https://doi.org/10.1002/pmic.200700003
https://doi.org/10.1002/pmic.200700003
Autor:
Ari Frank, Vineeth Surendranath, Andrej Shevchenko, Patrice Waridel, Henrik Thomas, Natalie Wielsch, Pavel A. Pevzner
Publikováno v:
Journal of Proteome Research. 5:2448-2456
Protein identifications with the borderline statistical confidence are typically produced by matching a few marginal quality MS/MS spectra to database peptide sequences and represent a significant bottleneck in the reliable and reproducible character
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35eeb08d99f8ab56af232d30ef8201c2
https://doi.org/10.1021/pr060200v
https://doi.org/10.1021/pr060200v
Publikováno v:
Journal of proteome research. 12(6)
Full-length de novo sequencing of unknown proteins remains a challenging open problem. Traditional methods that sequence spectra individually are limited by short peptide length, incomplete peptide fragmentation, and ambiguous de novo interpretations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::609e3aa852f5b9aa2f77c23635b0a0ca
https://pubmed.ncbi.nlm.nih.gov/23679345
https://pubmed.ncbi.nlm.nih.gov/23679345
Autor:
Ari Frank
Publikováno v:
Journal of proteome research. 8(5)
Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a comple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d169b21f3288d2428353c7028fd6d48e
https://pubmed.ncbi.nlm.nih.gov/19256476
https://pubmed.ncbi.nlm.nih.gov/19256476
Autor:
Ari Frank
Publikováno v:
Journal of proteome research. 8(5)
The analysis of the large volume of tandem mass spectrometry (MS/MS) proteomics data that is generated these days relies on automated algorithms that identify peptides from their mass spectra. An essential component of these algorithms is the scoring
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f05d4155a2a395a13b3aa9d21e8cad3
https://pubmed.ncbi.nlm.nih.gov/19231891
https://pubmed.ncbi.nlm.nih.gov/19231891
Autor:
Richard D. Smith, Steven P. Briggs, Nuno Bandeira, Pavel A. Pevzner, Zhouxin Shen, Stephen Tanner, Ari Frank
Tandem mass spectrometry (MS/MS) experiments often generate redundant data sets containing multiple spectra of the same peptides. Clustering of MS/MS spectra takes advantage of this redundancy by identifying multiple spectra of the same peptide and r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8bdac47686d4d8da89e50231fe2eb32
https://europepmc.org/articles/PMC2533155/
https://europepmc.org/articles/PMC2533155/
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America. 104(15)
Advances in tandem mass spectrometry (MS/MS) steadily increase the rate of generation of MS/MS spectra. As a result, the existing approaches that compare spectra against databases are already facing a bottleneck, particularly when interpreting spectr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8832cb265ce87fdab4a1bad722bf75d3
https://pubmed.ncbi.nlm.nih.gov/17404225
https://pubmed.ncbi.nlm.nih.gov/17404225