Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Raviteja, Vangara"'
Autor:
Azhar Khandekar, Raviteja Vangara, Mark Barnes, Marcos Díaz-Gay, Ammal Abbasi, Erik N. Bergstrom, Christopher D. Steele, Nischalan Pillay, Ludmil B. Alexandrov
Publikováno v:
BMC Genomics, Vol 24, Iss 1, Pp 1-9 (2023)
Abstract Background All cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fi
Externí odkaz:
https://doaj.org/article/e277fb79cb7e4bdb8efd3acb49845605
Autor:
Raviteja Vangara, Manish Bhattarai, Erik Skau, Gopinath Chennupati, Hristo Djidjev, Tom Tierney, James P. Smith, Valentin G. Stanev, Boian S. Alexandrov
Publikováno v:
IEEE Access, Vol 9, Pp 117217-117231 (2021)
Topic modeling, or identifying the set of topics that occur in a collection of articles, is one of the primary objectives of text mining. One of the big challenges in topic modeling is determining the correct number of topics: underestimating the num
Externí odkaz:
https://doaj.org/article/707c3e2add48470ab05fd9838d30a334
Autor:
S.M. Ashiqul Islam, Marcos Díaz-Gay, Yang Wu, Mark Barnes, Raviteja Vangara, Erik N. Bergstrom, Yudou He, Mike Vella, Jingwei Wang, Jon W. Teague, Peter Clapham, Sarah Moody, Sergey Senkin, Yun Rose Li, Laura Riva, Tongwu Zhang, Andreas J. Gruber, Christopher D. Steele, Burçak Otlu, Azhar Khandekar, Ammal Abbasi, Laura Humphreys, Natalia Syulyukina, Samuel W. Brady, Boian S. Alexandrov, Nischalan Pillay, Jinghui Zhang, David J. Adams, Iñigo Martincorena, David C. Wedge, Maria Teresa Landi, Paul Brennan, Michael R. Stratton, Steven G. Rozen, Ludmil B. Alexandrov
Publikováno v:
Cell genomics, vol 2, iss 11
Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d66650f68920d43fde2ce688d861fe80
https://escholarship.org/uc/item/9b82739r
https://escholarship.org/uc/item/9b82739r
Publikováno v:
Physical Review Research, Vol 2, Iss 2, p 023248 (2020)
Fractional Brownian motion (fBm) is a ubiquitous diffusion process in which the memory effects of the stochastic transport result in the mean-squared particle displacement following a power law 〈Δr^{2}〉∼t^{α}, where the diffusion exponent α
Externí odkaz:
https://doaj.org/article/ef46d722768f4240ab8a513696481e19
Autor:
Tongwu Zhang, Jian Sang, Phuc H. Hoang, Wei Zhao, Jennifer Rosenbaum, Leszek J. Klimczak, John McElderry, Alyssa Klein, Christopher Wirth, Erik N. Bergstrom, Marcos Díaz-Gay, Raviteja Vangara, Amy Hutchinson, Scott M. Lawrence, Nathan Cole, Bin Zhu, Teresa M. Przytycka, Jianxin Shi, Neil E. Caporaso, Robert Homer, Angela C. Pesatori, Dario Consonni, Stephen J. Chanock, David C. Wedge, Dmitry A. Gordenin, Ludmil B. Alexandrov, Reuben S. Harris, Maria Teresa Landi
Publikováno v:
Cancer Research. 83:1166-1166
APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of A
Publikováno v:
Large-Scale Scientific Computing ISBN: 9783030975487
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de4f7fb58bd1c2ca0de8c7f89fd5fd17
https://doi.org/10.1007/978-3-030-97549-4_39
https://doi.org/10.1007/978-3-030-97549-4_39
Publikováno v:
The Journal of Supercomputing. 76:7458-7488
The holistic analysis and understanding of the latent (that is, not directly observable) variables and patterns buried in large datasets is crucial for data-driven science, decision making and emergency response. Such exploratory analyses require dev
Autor:
S M Ashiqul, Islam, Marcos, Díaz-Gay, Yang, Wu, Mark, Barnes, Raviteja, Vangara, Erik N, Bergstrom, Yudou, He, Mike, Vella, Jingwei, Wang, Jon W, Teague, Peter, Clapham, Sarah, Moody, Sergey, Senkin, Yun Rose, Li, Laura, Riva, Tongwu, Zhang, Andreas J, Gruber, Christopher D, Steele, Burçak, Otlu, Azhar, Khandekar, Ammal, Abbasi, Laura, Humphreys, Natalia, Syulyukina, Samuel W, Brady, Boian S, Alexandrov, Nischalan, Pillay, Jinghui, Zhang, David J, Adams, Iñigo, Martincorena, David C, Wedge, Maria Teresa, Landi, Paul, Brennan, Michael R, Stratton, Steven G, Rozen, Ludmil B, Alexandrov
Publikováno v:
Cell genomics. 2(11)
Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for
Publikováno v:
Big Data III: Learning, Analytics, and Applications.
Clustering is an unsupervised machine learning technique that serves to extract patterns in unlabeled datasets by grouping their elements based on a similarity measure. A priori knowledge of the number of clusters is needed in most of the clustering
Autor:
Hristo N. Djidjev, Erik Skau, Boian S. Alexandrov, James P. Smith, Manish Bhattarai, Tom Tierney, Raviteja Vangara, Valentin Stanev, Gopinath Chennupati
Publikováno v:
IEEE Access, Vol 9, Pp 117217-117231 (2021)
Topic modeling, or identifying the set of topics that occur in a collection of articles, is one of the primary objectives of text mining. One of the big challenges in topic modeling is determining the correct number of topics: underestimating the num
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::307cd1f27e32f35faa42922f9c7de381