Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Raghu, Machiraju"'
Autor:
Ru M. Wen, Zhengyuan Qiu, G. Edward W. Marti, Eric E. Peterson, Fernando Jose Garcia Marques, Abel Bermudez, Yi Wei, Rosalie Nolley, Nathan Lam, Alex LaPat Polasko, Chun-Lung Chiu, Dalin Zhang, Sanghee Cho, Grigorios Marios Karageorgos, Elizabeth McDonough, Chrystal Chadwick, Fiona Ginty, Kyeong Joo Jung, Raghu Machiraju, Parag Mallick, Laura Crowley, Jonathan R. Pollack, Hongjuan Zhao, Sharon J. Pitteri, James D. Brooks
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-19 (2024)
Abstract Background Loss of AZGP1 expression is a biomarker associated with progression to castration resistance, development of metastasis, and poor disease-specific survival in prostate cancer. However, high expression of AZGP1 cells in prostate ca
Externí odkaz:
https://doaj.org/article/5a28bfe2f761406aa6383b764b9fb5d0
Autor:
Grigorios M. Karageorgos, Sanghee Cho, Elizabeth McDonough, Chrystal Chadwick, Soumya Ghose, Jonathan Owens, Kyeong Joo Jung, Raghu Machiraju, Robert West, James D. Brooks, Parag Mallick, Fiona Ginty
Publikováno v:
Frontiers in Bioinformatics, Vol 3 (2024)
Introduction: Prostate cancer is a highly heterogeneous disease, presenting varying levels of aggressiveness and response to treatment. Angiogenesis is one of the hallmarks of cancer, providing oxygen and nutrient supply to tumors. Micro vessel densi
Externí odkaz:
https://doaj.org/article/76f90f0b38a84f9db5dcbdb0a5e42308
Publikováno v:
ACS Omega, Vol 7, Iss 11, Pp 9465-9483 (2022)
Externí odkaz:
https://doaj.org/article/1d3eefa45cfa4b2495511f7a6a27b442
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-16 (2021)
Abstract Background Assigning chromatin states genome-wide (e.g. promoters, enhancers, etc.) is commonly performed to improve functional interpretation of these states. However, computational methods to assign chromatin state suffer from the followin
Externí odkaz:
https://doaj.org/article/dab4398a7edc424c9f8605a77b7eebc7
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S24, Pp 1-16 (2019)
Abstract Background Proteomic measurements, which closely reflect phenotypes, provide insights into gene expression regulations and mechanisms underlying altered phenotypes. Further, integration of data on proteome and transcriptome levels can valida
Externí odkaz:
https://doaj.org/article/08bc8c48c42543ad81b05381facb78c2
Autor:
Pacharmon Kaewprag, Cheryl Newton, Brenda Vermillion, Sookyung Hyun, Kun Huang, Raghu Machiraju
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 17, Iss S2, Pp 81-91 (2017)
Abstract Background We develop predictive models enabling clinicians to better understand and explore patient clinical data along with risk factors for pressure ulcers in intensive care unit patients from electronic health record data. Identifying ac
Externí odkaz:
https://doaj.org/article/67ae11d761144127822c241b8c00fbfb
Publikováno v:
Bioinform Adv
MotivationIntLIM uncovers phenotype-dependent linear associations between two types of analytes (e.g. genes and metabolites) in a multi-omic dataset, which may reflect chemically or biologically relevant relationships.ResultsThe new IntLIM R package
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::028a97780088ee853e1429920750ed12
https://doi.org/10.1093/bioadv/vbad009
https://doi.org/10.1093/bioadv/vbad009
Autor:
Tara Eicher, Garrett Kinnebrew, Andrew Patt, Kyle Spencer, Kevin Ying, Qin Ma, Raghu Machiraju, Ewy A. Mathé
Publikováno v:
Metabolites, Vol 10, Iss 5, p 202 (2020)
As researchers are increasingly able to collect data on a large scale from multiple clinical and omics modalities, multi-omics integration is becoming a critical component of metabolomics research. This introduces a need for increased understanding b
Externí odkaz:
https://doaj.org/article/97b385f195464012ae836a195ad60ee1
Autor:
Apan Qasem, Hartwig Anzt, Eduard Ayguade, Katharine Cahill, Ramon Canal, Jany Chan, Eric Fosler-Lussier, Fritz Gobel, Arpan Jain, Marcel Koch, Mateusz Kuzak, Josep Llosa, Raghu Machiraju, Xavier Martorell, Pratik Nayak, Shameema Oottikkal, Marcin Ostasz, Dhabaleswar K. Panda, Dirk Pleiter, Rajiv Ramnath, Maria-Ribera Sancho, Alessio Sclocco, Aamir Shafi, Hanno Spreeuw, Hari Subramoni, Karen Tomko
The lightning talks at EduHPC provide an opportunity to share early results and insights on parallel and distributed computing (PDC) education and training efforts. The four lightning talks at EduHPC 2022 cover a range of topics in broadening PDC edu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e04b2a95f605f31442e8019f41d9e01e
https://hdl.handle.net/2117/385362
https://hdl.handle.net/2117/385362
Autor:
Jie Wang, Shuli Xia, Brian Arand, Heng Zhu, Raghu Machiraju, Kun Huang, Hongkai Ji, Jiang Qian
Publikováno v:
PLoS Computational Biology, Vol 12, Iss 4, p e1004892 (2016)
Co-expression analysis has been employed to predict gene function, identify functional modules, and determine tumor subtypes. Previous co-expression analysis was mainly conducted at bulk tissue level. It is unclear whether co-expression analysis at t
Externí odkaz:
https://doaj.org/article/12e4f84d74c94a379817675912e30874