Zobrazeno 1 - 10
of 227
pro vyhledávání: '"Pathway prediction"'
Autor:
Gowri Nayar, Russ B. Altman
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 23, Iss , Pp 2727-2739 (2024)
Understanding protein-protein interactions (PPIs) and the pathways they comprise is essential for comprehending cellular functions and their links to specific phenotypes. Despite the prevalence of molecular data generated by high-throughput sequencin
Externí odkaz:
https://doaj.org/article/569e512a03a548b091b8536cd805a960
Autor:
Jasmin Hafner, Tim Lorsbach, Sebastian Schmidt, Liam Brydon, Katharina Dost, Kunyang Zhang, Kathrin Fenner, Jörg Wicker
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-9 (2024)
Abstract enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its in
Externí odkaz:
https://doaj.org/article/bf8efc5c7114488089507fb7a4cd5d48
Autor:
Alqurashi Abdulmajeed, Ahmad Waqar, Rahman Ziaur, Nawab Javed, Siddiqui Muhammad Faisal, Akbar Ali, Alkraiem Ayman Ahmad, Latif Muhammad
Publikováno v:
Open Chemistry, Vol 22, Iss 1, Pp 521-30 (2024)
This study applied a subtractive genomics approach to identify a potential drug target in the Porphyromonas gingivalis strain (ATCC BAA-308/W83). The aim was to characterize the whole proteome and hypothetical proteins (HPs) through structural, funct
Externí odkaz:
https://doaj.org/article/499cc69cfdac4a31af3d13394d5473bd
Autor:
Hyunwhan Joe, Hong-Gee Kim
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-15 (2024)
Abstract Background Metabolic pathway prediction is one possible approach to address the problem in system biology of reconstructing an organism’s metabolic network from its genome sequence. Recently there have been developments in machine learning
Externí odkaz:
https://doaj.org/article/053bec36905745f6946f4a92c67377b4
Autor:
Erik D. Huckvale, Hunter N. B. Moseley
Publikováno v:
Metabolites, Vol 14, Iss 11, p 582 (2024)
Background/Objectives: Predicting the biochemical pathway involvement of a compound could facilitate the interpretation of biological and biomedical research. Prior prediction approaches have largely focused on metabolism, training machine learning m
Externí odkaz:
https://doaj.org/article/f4b152c4f2b143d19f150fbdc8f10c3b
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-13 (2023)
Abstract Background Plant secondary metabolites are highly valued for their applications in pharmaceuticals, nutrition, flavors, and aesthetics. It is of great importance to elucidate plant secondary metabolic pathways due to their crucial roles in b
Externí odkaz:
https://doaj.org/article/266a575cb10a4e669461ebd5d2b0c55f
Autor:
Abdullah Tercan, Gıyasettin Özcan
Publikováno v:
Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, Vol 31, Iss 2, Pp 729-736 (2023)
Bu çalışmada literatürde yer alan ve uluslararası alanda öneme sahip olan GDSC veri kümesinde yer alan akciğer kanseri verileri toplanmış, ve bu veriler üzerinde yapay öğrenme yöntemleri kullanarak tahmin yapmak hedeflenmiştir. Bu ama
Externí odkaz:
https://doaj.org/article/d72f4b20f6e14bbdb25880825550a0a7
Publikováno v:
Frontiers in Nutrition, Vol 10 (2023)
IntroductionGreen banana flour can be used as a prebiotic due to its ability to promote gut health and provide several health benefits. In this study, we investigated whether feeding mice green banana flour at different doses would alter intestinal m
Externí odkaz:
https://doaj.org/article/d28b5e43d7d4486bbb2e515edd5e8f85
Autor:
Mariah V. Salcedo, Nathan Gravel, Abbas Keshavarzi, Liang-Chin Huang, Krzysztof J. Kochut, Natarajan Kannan
Publikováno v:
PeerJ, Vol 11, p e15815 (2023)
The 534 protein kinases encoded in the human genome constitute a large druggable class of proteins that include both well-studied and understudied “dark” members. Accurate prediction of dark kinase functions is a major bioinformatics challenge. H
Externí odkaz:
https://doaj.org/article/f9a6f8aea0fa42169043d7129c3f323f
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