Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Kyle Hippe"'
Autor:
Hasan Zulfiqar, Rida Sarwar Khan, Farwa Hassan, Kyle Hippe, Cassandra Hunt, Hui Ding, Xiao-Ming Song, Renzhi Cao
Publikováno v:
Mathematical Biosciences and Engineering, Vol 18, Iss 4, Pp 3348-3363 (2021)
N4-methylcytosine (4mC) is a kind of DNA modification which could regulate multiple biological processes. Correctly identifying 4mC sites in genomic sequences can provide precise knowledge about their genetic roles. This study aimed to develop an ens
Externí odkaz:
https://doaj.org/article/050d0ca07437494b8f5da19c9b1fc229
The Development of Machine Learning Methods in Discriminating Secretory Proteins of Malaria Parasite
Publikováno v:
Current Medicinal Chemistry. 29:807-821
Abstract: Malaria caused by Plasmodium falciparum is one of the major infectious diseases in the world. It is essential to exploit an effective method to predict secretory proteins of malaria parasites to develop effective cures and treatment. Bioche
Autor:
Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan
We seek to transform how new and emergent variants of pandemiccausing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eeb3062847bc49934d638fc48a21a278
https://doi.org/10.1101/2022.10.10.511571
https://doi.org/10.1101/2022.10.10.511571
Autor:
Ramanathan Arvind, Anda Trifan, Defne Ozgulbas, Alexander Brace, Kyle Hippe, Anima Anandkumar, Sarah Harris, Emad Tajkhorshid, John Stone
Publikováno v:
Journal of Biological Chemistry. 299:103443
Autor:
Ammaar Firozi, Minglei Zhao, Haowen Guan, Runbang Tang, Andrew Nakamura, Jie Hou, Dong Si, Kyle Hippe, Renzhi Cao
Publikováno v:
WIREs Computational Molecular Science. 12
Autor:
Sandra Montgomery, Renzhi Cao, Jie Hou, Nicola Justice, Joshua William Berkenpas, Hui Ding, Dong Si, Kyle Hippe, Noel Sigafoos, Cassandra Hunt, John Christian Oakley, Jacob Espinosa, Kiyomi Kishaba
Publikováno v:
Current gene therapy. 22(2)
With new developments in biomedical technology, it is now a viable therapeutic treatment to alter genes with techniques like CRISPR. At the same time, it is increasingly cheaper to perform whole genome sequencing, resulting in rapid advancement in ge
MotivationIt has been a challenge for biologists to determine 3D shapes of proteins from a linear chain of amino acids and understand how proteins carry out life’s tasks. Experimental techniques, such as X-ray crystallography or Nuclear Magnetic Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1a8b808618e88203c58a682f5945731
https://doi.org/10.1101/2021.01.28.428710
https://doi.org/10.1101/2021.01.28.428710
MotivationThe Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. When predictions are made for proteins of which we do not know the native structure, we run into an issue to tell how good a tertiary structur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62db6b3516b7195d1b09ac409ef88029
https://doi.org/10.1101/2021.01.28.428680
https://doi.org/10.1101/2021.01.28.428680
Publikováno v:
Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.
As the body of genomic product data increases at a much faster rate than can be annotated, computational analysis of protein function has never been more important. In this research, we introduce a novel protein function prediction method HMMeta, whi
Publikováno v:
Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics.
Predicting protein function from protein sequence is a main challenge in the computational biology field. Traditional methods that search protein sequences against existing databases may not work well in practice, particularly when little or no homol