Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Mingjian Jiang"'
Publikováno v:
PeerJ, Vol 11, p e16625 (2023)
Background A critical aspect of in silico drug discovery involves the prediction of drug-target affinity (DTA). Conducting wet lab experiments to determine affinity is both expensive and time-consuming, making it necessary to find alternative approac
Externí odkaz:
https://doaj.org/article/66f6eeaeb23b4825a353d47f994210d1
Autor:
Shugang Zhang, Weigang Lu, Fei Yang, Zhen Li, Shuang Wang, Mingjian Jiang, Xiaofeng Wang, Zhiqiang Wei
Publikováno v:
npj Systems Biology and Applications, Vol 8, Iss 1, Pp 1-17 (2022)
Abstract Short QT syndrome (SQTS) is a rare but dangerous genetic disease. In this research, we conducted a comprehensive in silico investigation into the arrhythmogenesis in KCNH2 T618I-associated SQTS using a multi-scale human ventricle model. A Ma
Externí odkaz:
https://doaj.org/article/f9f920d3b4714e179849e30640670834
Publikováno v:
BMC Genomics, Vol 23, Iss 1, Pp 1-17 (2022)
Abstract Background Affinity prediction between molecule and protein is an important step of virtual screening, which is usually called drug-target affinity (DTA) prediction. Its accuracy directly influences the progress of drug development. Sequence
Externí odkaz:
https://doaj.org/article/aaf54e48a5e44472921803089d2331e6
Publikováno v:
IEEE Access, Vol 8, Pp 18601-18614 (2020)
Molecular property prediction is important to drug design. With the development of artificial intelligence, deep learning methods are effective for extracting molecular features. In this paper, we propose a multichannel substructure-graph gated recur
Externí odkaz:
https://doaj.org/article/e43c5c1588c0481e8da858ce8e290028
Publikováno v:
Applied Sciences, Vol 13, Iss 2, p 802 (2023)
The channel attention mechanism is widely used in deep learning. However, the existing channel attention mechanism directly performs the global average pooling and then full connection for all channels, which causes the local information to be ignore
Externí odkaz:
https://doaj.org/article/ccafd0f6920148178070964ea1d86f55
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-13 (2019)
Abstract Background Binding sites are the pockets of proteins that can bind drugs; the discovery of these pockets is a critical step in drug design. With the help of computers, protein pockets prediction can save manpower and financial resources. Res
Externí odkaz:
https://doaj.org/article/afe2741199c545a597e050601435a491
Autor:
Rihong Wang, Ziyu Li, Lingzhi Yang, Yuming Li, Hao Zhang, Chuanwang Song, Mingjian Jiang, Xiaoyun Ye, Keyong Hu
Publikováno v:
Applied Sciences, Vol 12, Iss 15, p 7823 (2022)
In the steelmaking industry, the state of the blast furnace tuyere is an important basis for obtaining the internal information of the blast furnace. Traditional detections mainly rely on manual experience judgment, which is a time-consuming and tiri
Externí odkaz:
https://doaj.org/article/f544020b029348fc95ed476f7cba2670
Publikováno v:
Biomolecules, Vol 11, Iss 8, p 1119 (2021)
In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. Howeve
Externí odkaz:
https://doaj.org/article/8723ee1337b94baf902b53a69f979518
Publikováno v:
IEEE Access, Vol 8, Pp 127968-127968 (2020)
In the above article [1], there are two errors in Figures 8 and 19. The error of Figure 8 was caused by incorrectly referencing the same figure as Figure 9.
Externí odkaz:
https://doaj.org/article/d6c2fa3169744e82a28c4a63bb453108
Publikováno v:
Molecules, Vol 24, Iss 18, p 3383 (2019)
Molecular toxicity prediction is one of the key studies in drug design. In this paper, a deep learning network based on a two-dimension grid of molecules is proposed to predict toxicity. At first, the van der Waals force and hydrogen bond were calcul
Externí odkaz:
https://doaj.org/article/dd8bfc95a9814de38b002c76726a2b96