Zobrazeno 1 - 10
of 55
pro vyhledávání: '"Naveen Sivadasan"'
Autor:
Sarah L. Stenton, Melanie C. O’Leary, Gabrielle Lemire, Grace E. VanNoy, Stephanie DiTroia, Vijay S. Ganesh, Emily Groopman, Emily O’Heir, Brian Mangilog, Ikeoluwa Osei-Owusu, Lynn S. Pais, Jillian Serrano, Moriel Singer-Berk, Ben Weisburd, Michael W. Wilson, Christina Austin-Tse, Marwa Abdelhakim, Azza Althagafi, Giulia Babbi, Riccardo Bellazzi, Samuele Bovo, Maria Giulia Carta, Rita Casadio, Pieter-Jan Coenen, Federica De Paoli, Matteo Floris, Manavalan Gajapathy, Robert Hoehndorf, Julius O. B. Jacobsen, Thomas Joseph, Akash Kamandula, Panagiotis Katsonis, Cyrielle Kint, Olivier Lichtarge, Ivan Limongelli, Yulan Lu, Paolo Magni, Tarun Karthik Kumar Mamidi, Pier Luigi Martelli, Marta Mulargia, Giovanna Nicora, Keith Nykamp, Vikas Pejaver, Yisu Peng, Thi Hong Cam Pham, Maurizio S. Podda, Aditya Rao, Ettore Rizzo, Vangala G. Saipradeep, Castrense Savojardo, Peter Schols, Yang Shen, Naveen Sivadasan, Damian Smedley, Dorian Soru, Rajgopal Srinivasan, Yuanfei Sun, Uma Sunderam, Wuwei Tan, Naina Tiwari, Xiao Wang, Yaqiong Wang, Amanda Williams, Elizabeth A. Worthey, Rujie Yin, Yuning You, Daniel Zeiberg, Susanna Zucca, Constantina Bakolitsa, Steven E. Brenner, Stephanie M. Fullerton, Predrag Radivojac, Heidi L. Rehm, Anne O’Donnell-Luria
Publikováno v:
Human Genomics, Vol 18, Iss 1, Pp 1-25 (2024)
Abstract Background A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wi
Externí odkaz:
https://doaj.org/article/29fbe7d26d88463789f004c8908aa4a7
Autor:
Aditya Rao, Thomas Joseph, Vangala G Saipradeep, Sujatha Kotte, Naveen Sivadasan, Rajgopal Srinivasan
Publikováno v:
PLoS ONE, Vol 15, Iss 4, p e0231728 (2020)
IntroductionPhenotype-driven rare disease gene prioritization relies on high quality curated resources containing disease, gene and phenotype annotations. However, the effectiveness of gene prioritization tools is constrained by the incomplete covera
Externí odkaz:
https://doaj.org/article/223c1bbf46bc4a2aadb4a443644a9360
Autor:
Aditya Rao, Saipradeep VG, Thomas Joseph, Sujatha Kotte, Naveen Sivadasan, Rajgopal Srinivasan
Publikováno v:
BMC Medical Genomics, Vol 11, Iss 1, Pp 1-12 (2018)
Abstract Background One of the major goals of genomic medicine is the identification of causal genomic variants in a patient and their relation to the observed clinical phenotypes. Prioritizing the genomic variants by considering only the genotype in
Externí odkaz:
https://doaj.org/article/2f226c2edccf47bc8554e5da314add54
Autor:
Vidushi Walia, Sujatha Kotte, Naveen Sivadasan, Hrishikesh Sharma, Thomas Joseph, Binuja Varma, Geetashree Mukherjee, V.G Saipradeep
Advanced image processing methods have shown promise in computational pathology, including the extraction of crucial microscopic features from histology images. Accurate detection and classification of cell nuclei from whole-slide images (WSI) play a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16a869e107c8e6dd7077e6841cf0a077
https://doi.org/10.1101/2023.05.10.540156
https://doi.org/10.1101/2023.05.10.540156
Supplementary Material - MAGE: Strain Level Profiling of Metagenome Samples
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6c894084b5bb6952a4626964e5b8021
Autor:
Sujatha Kotte, VG Saipradeep, Naveen Sivadasan, Thomas Joseph, Hrishikesh Sharma, Vidushi Walia, Binuja Varma, Geetashree Mukherjee
Publikováno v:
Mitosis Domain Generalization and Diabetic Retinopathy Analysis ISBN: 9783031336577
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5b990a05477623d6b062999ff0f42c3
https://doi.org/10.1007/978-3-031-33658-4_23
https://doi.org/10.1007/978-3-031-33658-4_23
Metagenomic profiling from sequencing data aims to disentangle a microbial sample at lower ranks of taxonomy, such as species and strains. Deep taxonomic profiling involving accurate estimation of strain level abundances aids in precise quantificatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70543ea8676c59b54a83f46fdfcda70f
https://doi.org/10.1101/2022.11.24.517382
https://doi.org/10.1101/2022.11.24.517382
Autor:
Qingyu Chen, Alexis Allot, Robert Leaman, Rezarta Islamaj, Jingcheng Du, Li Fang, Kai Wang, Shuo Xu, Yuefu Zhang, Parsa Bagherzadeh, Sabine Bergler, Aakash Bhatnagar, Nidhir Bhavsar, Yung-Chun Chang, Sheng-Jie Lin, Wentai Tang, Hongtong Zhang, Ilija Tavchioski, Senja Pollak, Shubo Tian, Jinfeng Zhang, Yulia Otmakhova, Antonio Jimeno Yepes, Hang Dong, Honghan Wu, Richard Dufour, Yanis Labrak, Niladri Chatterjee, Kushagri Tandon, Fréjus A A Laleye, Loïc Rakotoson, Emmanuele Chersoni, Jinghang Gu, Annemarie Friedrich, Subhash Chandra Pujari, Mariia Chizhikova, Naveen Sivadasan, Saipradeep VG, Zhiyong Lu
Publikováno v:
Database-The journal of Biological Databases and Curation
Database-The journal of Biological Databases and Curation, 2022, 2022, ⟨10.1093/database/baac069⟩
Database (Oxford)
Chen, Q, Allot, A, Leaman, R, Islamaj, R, Du, J, Fang, L, Wang, K, Xu, S, Zhang, Y, Bagherzadeh, P, Bergler, S, Bhatnagar, A, Bhavsar, N, Chang, Y-C, Lin, S-J, Tang, W, Zhang, H, Tavchioski, I, Pollak, S, Tian, S, Zhang, J, Otmakhova, Y, Yepes, A J, Dong, H, Wu, H, Dufour, R, Labrak, Y, Chatterjee, N, Tandon, K, Laleye, F A A, Rakotoson, L, Chersoni, E, Gu, J, Friedrich, A, Pujari, S C, Chizhikova, M, Sivadasan, N, Vg, S & Lu, Z 2022, ' Multi-label classification for biomedical literature : an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations ', Database : the journal of biological databases and curation, vol. 2022 . https://doi.org/10.1093/database/baac069
Database-The journal of Biological Databases and Curation, 2022, 2022, ⟨10.1093/database/baac069⟩
Database (Oxford)
Chen, Q, Allot, A, Leaman, R, Islamaj, R, Du, J, Fang, L, Wang, K, Xu, S, Zhang, Y, Bagherzadeh, P, Bergler, S, Bhatnagar, A, Bhavsar, N, Chang, Y-C, Lin, S-J, Tang, W, Zhang, H, Tavchioski, I, Pollak, S, Tian, S, Zhang, J, Otmakhova, Y, Yepes, A J, Dong, H, Wu, H, Dufour, R, Labrak, Y, Chatterjee, N, Tandon, K, Laleye, F A A, Rakotoson, L, Chersoni, E, Gu, J, Friedrich, A, Pujari, S C, Chizhikova, M, Sivadasan, N, Vg, S & Lu, Z 2022, ' Multi-label classification for biomedical literature : an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations ', Database : the journal of biological databases and curation, vol. 2022 . https://doi.org/10.1093/database/baac069
The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature—at a rate of about 10 000 article
Autor:
Zhiqiang Hu, Jesse M. Hunter, Olivier Lichtarge, Sean D. Mooney, Aashish N. Adhikari, Steven E. Brenner, Rita Casadio, Yizhou Yin, Lipika R. Pal, Uma Sunderam, Panagiotis Katsonis, Predrag Radivojac, Thomas Joseph, Giulia Babbi, Naveen Sivadasan, Constantina Bakolitsa, Vangala G. Saipradeep, Laura Kasak, John Moult, Julian Gough, M. Stephen Meyn, Pier Luigi Martelli, Jennifer Poitras, Rupa A Udani, Jan Zaucha, Rafael F. Guerrero, Yuxiang Jiang, Aditya Rao, Sujatha Kotte, Kunal Kundu
Publikováno v:
Hum Mutat
Whole-genome sequencing (WGS) holds great potential as a diagnostic test. However, the majority of patients currently undergoing WGS lack a molecular diagnosis, largely due to the vast number of undiscovered disease genes and our inability to assess
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779795
ICCS (6)
ICCS (6)
Linear regression is a popular machine learning approach to learn and predict real valued outputs or dependent variables from independent variables or features. In many real world problems, its beneficial to perform sparse linear regression to identi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d62fc21213582b7b1c8d8b271ff02b4
https://doi.org/10.1007/978-3-030-77980-1_8
https://doi.org/10.1007/978-3-030-77980-1_8