Výsledky vyhledávání - "Robert L Grossman"

Akademický článek

Towards self-describing and FAIR bulk formats for biomedical data.

Autor: Michael Lukowski, Andrew Prokhorenkov, Robert L Grossman

Publikováno v: PLoS Computational Biology, Vol 19, Iss 3, p e1010944 (2023)

We introduce a self-describing serialized format for bulk biomedical data called the Portable Format for Biomedical (PFB) data. The Portable Format for Biomedical data is based upon Avro and encapsulates a data model, a data dictionary, the data itse

Externí odkaz: https://doaj.org/article/8a7a3420a4694f04813e7094919c66d4

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Akademický článek

From biomedical cloud platforms to microservices: next steps in FAIR data and analysis

Autor: Nathan C. Sheffield, Vivien R. Bonazzi, Philip E. Bourne, Tony Burdett, Timothy Clark, Robert L. Grossman, Ola Spjuth, Andrew D. Yates

Publikováno v: Scientific Data, Vol 9, Iss 1, Pp 1-8 (2022)

The biomedical research community is investing heavily in biomedical cloud platforms. Cloud computing holds great promise for addressing challenges with big data and ensuring reproducibility in biology. However, despite their advantages, cloud platfo

Externí odkaz: https://doaj.org/article/c867a7846612472da5e21de4897cece0

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Akademický článek

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN

Autor: Xingyan Kuang, Fan Wang, Kyle M. Hernandez, Zhenyu Zhang, Robert L. Grossman

Publikováno v: Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)

Abstract Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial

Externí odkaz: https://doaj.org/article/1347de2f4d0b452aaf80f1843aa97d2f

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Akademický článek

The impact of site-specific digital histology signatures on deep learning model accuracy and bias

Autor: Frederick M. Howard, James Dolezal, Sara Kochanny, Jefree Schulte, Heather Chen, Lara Heij, Dezheng Huo, Rita Nanda, Olufunmilayo I. Olopade, Jakob N. Kather, Nicole Cipriani, Robert L. Grossman, Alexander T. Pearson

Publikováno v: Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021)

Deep learning models have been trained on The Cancer Genome Atlas to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. Here, the authors demonstrate that site-specific histologic si

Externí odkaz: https://doaj.org/article/63d9acc99eb6472c87b682f300c925c8

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Akademický článek

Uniform genomic data analysis in the NCI Genomic Data Commons

Autor: Zhenyu Zhang, Kyle Hernandez, Jeremiah Savage, Shenglai Li, Dan Miller, Stuti Agrawal, Francisco Ortuno, Louis M. Staudt, Allison Heath, Robert L. Grossman

Publikováno v: Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)

The Genomic Data Commons repository contains genomic, epigenomic, proteomic and clinical data from the TCGA and TARGET datasets. Here, the authors describe the analysis methods for how these divergent datasets were integrated together.

Externí odkaz: https://doaj.org/article/6b96ad04560f436984a85fdec0836132

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Akademický článek

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space

Autor: Michael C. Schatz, Anthony A. Philippakis, Enis Afgan, Eric Banks, Vincent J. Carey, Robert J. Carroll, Alessandro Culotti, Kyle Ellrott, Jeremy Goecks, Robert L. Grossman, Ira M. Hall, Kasper D. Hansen, Jonathan Lawson, Jeffrey T. Leek, Anne O’Donnell Luria, Stephen Mosher, Martin Morgan, Anton Nekrutenko, Brian D. O’Connor, Kevin Osborn, Benedict Paten, Candace Patterson, Frederick J. Tan, Casey Overby Taylor, Jennifer Vessio, Levi Waldron, Ting Wang, Kristin Wuichet, Alexander Baumann, Andrew Rula, Anton Kovalsy, Clare Bernard, Derek Caetano-Anollés, Geraldine A. Van der Auwera, Justin Canas, Kaan Yuksel, Kate Herman, M. Morgan Taylor, Marianie Simeon, Michael Baumann, Qi Wang, Robert Title, Ruchi Munshi, Sushma Chaluvadi, Valerie Reeves, William Disman, Salin Thomas, Allie Hajian, Elizabeth Kiernan, Namrata Gupta, Trish Vosburg, Ludwig Geistlinger, Marcel Ramos, Sehyun Oh, Dave Rogers, Frances McDade, Mim Hastie, Nitesh Turaga, Alexander Ostrovsky, Alexandru Mahmoud, Dannon Baker, Dave Clements, Katherine E.L. Cox, Keith Suderman, Nataliya Kucher, Sergey Golitsynskiy, Samantha Zarate, Sarah J. Wheelan, Kai Kammers, Ana Stevens, Carolyn Hutter, Christopher Wellington, Elena M. Ghanaim, Ken L. Wiley, Jr., Shurjo K. Sen, Valentina Di Francesco, Deni s Yuen, Brian Walsh, Luke Sargent, Vahid Jalili, John Chilton, Lori Shepherd, B.J. Stubbs, Ash O’Farrell, Benton A. Vizzier, Jr., Charles Overbeck, Charles Reid, David Charles Steinberg, Elizabeth A. Sheets, Julian Lucas, Lon Blauvelt, Louise Cabansay, Noah Warren, Brian Hannafious, Tim Harris, Radhika Reddy, Eric Torstenson, M. Katie Banasiewicz, Haley J. Abel, Jason Walker

Publikováno v: Cell Genomics, Vol 2, Iss 1, Pp 100085- (2022)

Summary: The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, managemen

Externí odkaz: https://doaj.org/article/95ac1623e901491c821d128f529da364

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