Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Farshid Rayhan"'
Publikováno v:
Heliyon, Vol 6, Iss 3, Pp e03444- (2020)
The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto-encoder based feature manipulation and a convolutional neural network based classifi
Externí odkaz:
https://doaj.org/article/e58549e5544546d4882c9c5dceb769c0
Publikováno v:
Journal of Theoretical Biology. 464:1-8
Drug target interaction prediction is a very labor-intensive and expensive experimental process which has motivated researchers to focus on in silico prediction to provide information on potential interaction. In recent years, researchers have propos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b2fea73f42520a787466192e19e9f87
https://doi.org/10.1016/j.jtbi.2018.12.024
https://doi.org/10.1016/j.jtbi.2018.12.024
We introduce a new architecture called ChoiceNet where each layer of the network is highly connected with skip connections and channelwise concatenations. This enables the network to alleviate the problem of vanishing gradients, reduces the number of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa84280b05983a82ee03a50ad423db38
http://arxiv.org/abs/1904.09472
http://arxiv.org/abs/1904.09472
Publikováno v:
Heliyon
Heliyon, Vol 6, Iss 3, Pp e03444-(2020)
Heliyon, Vol 6, Iss 3, Pp e03444-(2020)
The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto-encoder based feature manipulation and a convolutional neural network based classifi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d8f6eb761cf41a5b54dee957a1eb8f4
https://pubmed.ncbi.nlm.nih.gov/32154410
https://pubmed.ncbi.nlm.nih.gov/32154410
Autor:
Swakkhar Shatabda, Dewan Md. Farid, Md. Rafsan Jani, Farshid Rayhan, Asif Mahbub, Sajid Ahmed
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811314971
The problem of class imbalance along with class overlapping has become a major issue in the domain of supervised learning. Most classification algorithms assume equal cardinality of the classes under consideration while optimising the cost function,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79649aca49083f199936bf7ffe85a34a
https://doi.org/10.1007/978-981-13-1498-8_12
https://doi.org/10.1007/978-981-13-1498-8_12
Autor:
Zaynab Mousavian, Sajid Ahmed, Swakkhar Shatabda, Dewan Md. Farid, Abdollah Dehzangi, M. Sohel Rahman, Farshid Rayhan
Publikováno v:
Scientific Reports
Scientific Reports, Vol 7, Iss 1, Pp 1-18 (2017)
Scientific Reports, Vol 7, Iss 1, Pp 1-18 (2017)
Prediction of new drug-target interactions is extremely important as it can lead the researchers to find new uses for old drugs and to realize the therapeutic profiles or side effects thereof. However, experimental prediction of drug-target interacti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4aee1daecd2acb9ee51874979a14c0d7
https://doi.org/10.1038/s41598-017-18025-2
https://doi.org/10.1038/s41598-017-18025-2
Autor:
Farshid Rayhan, Asif Mahbub, Sajid Ahmed, Md. Rafsan Jani, Swakkhar Shatabda, Dewan Md. Farid, Chowdhury Mofizur Rahman
Publikováno v:
SKIMA
Class imbalance problem has been a challenging research problem in the fields of machine learning and data mining as most real life datasets are imbalanced. Several existing machine learning algorithms try to maximize the accuracy classification by c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb48eeaaedda9495cab1b6a5a81aa32b
http://arxiv.org/abs/1712.06658
http://arxiv.org/abs/1712.06658
Publikováno v:
2017 2nd International Conference on Computational Systems and Information Technology for Sustainable Solution (CSITSS).
Class imbalance classification has become a dominant problem in supervised learning. The bias of majority class instances dominates in quantity over minority class instances in imbalanced datasets, which produce the suboptimal classification results
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e93be9b76f8f6cfad949ccb49d390bb8
https://doi.org/10.1109/csitss.2017.8447799
https://doi.org/10.1109/csitss.2017.8447799
Class imbalance classification is a challenging research problem in data mining and machine learning, as most of the real-life datasets are often imbalanced in nature. Existing learning algorithms maximise the classification accuracy by correctly cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3be3d5ff4bdb2c6d39370df9673ae974