Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Manato Akiyama"'
Publikováno v:
Journal of Cheminformatics, Vol 16, Iss 1, Pp 1-12 (2024)
Abstract Motivation Computational techniques for drug-disease prediction are essential in enhancing drug discovery and repositioning. While many methods utilize multimodal networks from various biological databases, few integrate comprehensive multi-
Externí odkaz:
https://doaj.org/article/d6551e4582384ec6bf08a983ed7fe1bc
Autor:
Toshiki Ochiai, Tensei Inukai, Manato Akiyama, Kairi Furui, Masahito Ohue, Nobuaki Matsumori, Shinsuke Inuki, Motonari Uesugi, Toshiaki Sunazuka, Kazuya Kikuchi, Hideaki Kakeya, Yasubumi Sakakibara
Publikováno v:
Communications Chemistry, Vol 6, Iss 1, Pp 1-14 (2023)
Abstract The structural diversity of chemical libraries, which are systematic collections of compounds that have potential to bind to biomolecules, can be represented by chemical latent space. A chemical latent space is a projection of a compound str
Externí odkaz:
https://doaj.org/article/e5457904f4f54e489f843f4e0261fb18
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
Accurately predicting the secondary structure of non-coding RNAs can help unravel their function. Here the authors propose a method integrating thermodynamic information and deep learning to improve the robustness of RNA secondary structure predictio
Externí odkaz:
https://doaj.org/article/862e961ec971484fbb3f7229d26241f6
Autor:
Toshiki Ochiai, Tensei Inukai, Manato Akiyama, Kairi Furui, Masahito Ohue, Nobuaki Matsumori, Shinsuke Inuki, Motonari Uesugi, Toshiaki Sunazuka, Kazuya Kikuchi, Hideaki Kakeya, Yasubumi Sakakibara
The structural diversity of chemical libraries, which are systematic collections of compounds that have potential to bind to biomolecules, can be represented by chemical latent space. A chemical latent space is a projection of a compound structure in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8c168523f29e345bc2c613fa98e8dfa
https://doi.org/10.26434/chemrxiv-2023-pjl0w-v2
https://doi.org/10.26434/chemrxiv-2023-pjl0w-v2
Autor:
Toshiki Ochiai, Tensei Inukai, Manato Akiyama, Kairi Furui, Masahito Ohue, Nobuaki Matsumori, Shinsuke Inuki, Motonari Uesugi, Toshiaki Sunazuka, Kazuya Kikuchi, Hideaki Kakeya, Yasubumi Sakakibara
The structural diversity of chemical libraries, which are systematic collections of compounds that have potential to bind to biomolecules, can be represented by chemical latent space. A chemical latent space is a projection of a compound structure in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98430c3302a7f38e0e939eae4420d49e
https://doi.org/10.26434/chemrxiv-2023-pjl0w
https://doi.org/10.26434/chemrxiv-2023-pjl0w
Autor:
Manato Akiyama, Kengo Sato
Publikováno v:
Methods in Molecular Biology ISBN: 9781071627679
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9d7e1bba92ba5ed264f60d4b6b15c09
https://doi.org/10.1007/978-1-0716-2768-6_6
https://doi.org/10.1007/978-1-0716-2768-6_6
Publikováno v:
Genes; Volume 13; Issue 11; Pages: 2155
Existing approaches to predicting RNA secondary structures depend on how the secondary structure is decomposed into substructures, that is, the architecture, to define their parameter space. However, architecture dependency has not been sufficiently
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c6386b1d5eafd22cb38c739364be4fb
https://pubmed.ncbi.nlm.nih.gov/36421829
https://pubmed.ncbi.nlm.nih.gov/36421829
Autor:
Manato Akiyama, Yasubumi Sakakibara
Publikováno v:
NAR genomics and bioinformatics. 4(1)
Effective embedding is actively conducted by applying deep learning to biomolecular information. Obtaining better embeddings enhances the quality of downstream analyses, such as DNA sequence motif detection and protein function prediction. In this st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad05fd95f29d0afdde40fbe68a2d3f37
https://pubmed.ncbi.nlm.nih.gov/35211670
https://pubmed.ncbi.nlm.nih.gov/35211670
Autor:
Manato Akiyama, Yasubumi Sakakibara
Effective embedding is being actively conducted by applying deep learning to biomolecular information. Obtaining better embedding enhances the quality of downstream analysis such as DNA sequence motif detection and protein function prediction. In thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f0ef7f2a2c5bcaaf348541fd98f99ec
https://doi.org/10.1101/2021.08.23.457433
https://doi.org/10.1101/2021.08.23.457433
Publikováno v:
Bioinformatics Advances. 1
Motivation Biological sequence classification is the most fundamental task in bioinformatics analysis. For example, in metagenome analysis, binning is a typical type of DNA sequence classification. In order to classify sequences, it is necessary to d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67010b44a9ed9eb613634257bf4f8731
https://doi.org/10.1093/bioadv/vbab039
https://doi.org/10.1093/bioadv/vbab039