N
Nita Deshpande
Researcher at University of California, San Diego
Publications - 5
Citations - 531
Nita Deshpande is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Protein Data Bank & Protein Data Bank (RCSB PDB). The author has an hindex of 4, co-authored 4 publications receiving 513 citations.
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Journal ArticleDOI
The RCSB Protein Data Bank: a redesigned query system and relational database based on the mmCIF schema
Nita Deshpande,Kenneth J. Addess,Wolfgang F. Bluhm,Jeffrey C. Merino-Ott,Wayne Townsend-Merino,Qing-qing Zhang,Charlie Knezevich,Lie-jun Xie,Li Chen,Zukang Feng,Rachel Kramer Green,Judith L. Flippen-Anderson,John D. Westbrook,Helen M. Berman,Philip E. Bourne +14 more
TL;DR: The Research Collaboratory for Structural Bioinformatics (RCSB) has completely redesigned its resource for the distribution and query of 3D structure data, expanding the functionality of the existing site by providing structure data in greater detail and uniformity, improved query and enhanced analysis tools.
Journal ArticleDOI
The distribution and query systems of the RCSB Protein Data Bank
Philip E. Bourne,Kenneth J. Addess,Wolfgang F. Bluhm,Li Chen,Nita Deshpande,Zukang Feng,Ward Fleri,Rachel Kramer Green,Jeffrey C. Merino-Ott,Wayne Townsend-Merino,Helge Weissig,John D. Westbrook,Helen M. Berman +12 more
TL;DR: The current query and distribution system is described and an alpha version of the future re-engineered system introduced.
Proceedings ArticleDOI
Intrinsic evaluation of text mining tools may not predict performance on realistic tasks
J. Gregory Caporaso,Nita Deshpande,J. Lynn Fink,Philip E. Bourne,K. Bretonnel Cohen,Lawrence Hunter +5 more
TL;DR: It is found that high performance on gold standard data does not necessarily translate to high performance for database annotation in intrinsic versus extrinsic evaluations, and it is concluded that currently the most cost-effective and reliable approach for database annotations might incorporate manual and automatic annotation methods.
Book ChapterDOI
The Research Collaboratory for Structural Bioinformatics Protein Data Bank
Philip E. Bourne,Wolfgang F. Bluhm,Nita Deshpande,Q. Zhang,Helen M. Berman,Judith L. Flippen-Anderson +5 more
TL;DR: This chapter describes the procedures and resources involving the PDB archives that are particular to the Research Collaboratory for Structural Bioinformatics (RCSB PDB), one of the three members of the wwPDB.
Journal ArticleDOI
Investigation of hypertension and type 2 diabetes as risk factors for dementia in the All of Us cohort
Shashwat Deepali Nagar,Jun Qian,Eric Boerwinkle,Mine Cicek,Cheryl R. Clark,Elizabeth Cohn,Kelly A. Gebo,Roxana Loperena,Kelsey R. Mayo,Stephen C. Mockrin,Lucila Ohno-Machado,Andrea H. Ramirez,Sheri D. Schully,Ashley Able,Ashley K. Green,Priscilla Pemu,Alexander Quarshie,Kelley Carroll,Lawrence L. Sanders,Howard Mosby,Elizabeth Olorundare,Atuarra McCaslin,Chadrick Anderson,Andrea N Pearson,K. C. Igwe,Karunamuni Silva,Gwen Daugett,Jason McCray,Michael Prude,Cheryl Franklin,Stephan Zuchner,Olveen Carrasquillo,Rosario Isasi,Jacob L. McCauley,J. G. Melo,Ana K. Riccio,Patrice L. Whitehead,Patricia Guzmán,Christina Gladfelter,Rebecca Velez,Mario Saporta,Brandon Apagüeño,Lisa Abreu,Betsy Shenkman,Bill Hogan,Eileen M. Handberg,Jamie Hensley,Sonya H. White,Brittney Roth-Manning,Tona Mendoza,Alexander Loiacono,Donny Weinbrenner,Mahmoud Enani,Ali Nouina,Michael E. Zwick,Tracie C. Rosser,Arshed A. Quyyumi,Theodore M. Johnson,Greg S. Martin,Alvaro Alonso,Tina Thompson,Nita Deshpande,Henry Richard Johnston,Hina Ahmed,Letheshia Husbands,I. King Jordan,Robert Meller +66 more
TL;DR: In this paper , a cross-sectional analysis of participant data from the All of Us (AoU) Research Program, a large observational cohort study of US residents, was conducted to compare the prevalence of dementia, hypertension, and T2D in the AoU cohort to previously reported prevalence values for the US population.