Maha A. Thafar
Maha A. Thafar
Assistant Professor, Collage of computers & information technology, Taif University, KUAST Alumni
Vahvistettu sähköpostiosoite verkkotunnuksessa - Kotisivu
Comparison Study of Computational Prediction Tools for Drug-Target Binding Affinities
MA Thafar, AB Raies, S Albaradei, M Essack, VB Bajic
Frontiers in Chemistry 7, 782, 2019
DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques
MA Thafar, RS Olayan, H Ashoor, S Albaradei, VB Bajic, X Gao, ...
Journal of Cheminformatics 12 (1), 1-17, 2020
Machine Learning and Deep Learning Methods that use Omics Data for Metastasis Prediction
S Albaradei, MA Thafar, A Alsaedi, C Van Neste, T Gojobori, M Essack, ...
Computational and Structural Biotechnology Journal, 2021
Splice2Deep: An ensemble of deep convolutional neural networks for improved splice site prediction in genomic DNA
S Albaradei, A Magana-Mora, MA Thafar, M Uludag, VB Bajic, T Gojobori, ...
Gene: X, 100035, 2020
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
MA Thafar, RS Olayan, S Albaradei, VB Bajic, T Gojobori, M Essack, ...
Journal of cheminformatics 13 (1), 1-18, 2021
StackACPred: Prediction of anticancer peptides by integrating optimized multiple feature descriptors with stacked ensemble approach
M Arif, S Ahmed, F Ge, M Kabir, YD Khan, DJ Yu, M Thafar
Chemometrics and Intelligent Laboratory Systems 220, 104458, 2022
Application and evaluation of knowledge graph embeddings in biomedical data
M Alshahrani, MA Thafar, M Essack
PeerJ Computer Science 7, e341, 2021
Towards Formal Multimodal Analysis of Emotions for Affective Computing.
M Ghayoumi, MA Thafar, AK Bansal
DMS, 48-54, 2016
MetaCancer: A deep learning-based pan-cancer metastasis prediction model developed using multi-omics data
S Albaradei, F Napolitano, MA Thafar, T Gojobori, M Essack, X Gao
Computational and Structural Biotechnology Journal 19, 4404-4411, 2021
Combining biomedical knowledge graphs and text to improve predictions for drug-target interactions and drug-indications
M Alshahrani, A Almansour, A Alkhaldi, MA Thafar, M Uludag, M Essack, ...
PeerJ 10, e13061, 2022
Comparison study of computational prediction tools for drug-target binding affinities. Front Chem. 2019; 7: 782
M Thafar, AB Raies, S Albaradei, M Essack, VB Bajic
Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning
MA Thafar, M Alshahrani, S Albaradei, T Gojobori, M Essack, X Gao
Scientific reports 12 (1), 4751, 2022
Automated counting of colony forming units using deep transfer learning from a model for congested scenes analysis
S Albaradei, F Napolitano, M Uludag, MA Thafar, S Napolitano, M Essack, ...
IEEE Access, 2020
Metastatic State of Colorectal Cancer can be Accurately Predicted with Methylome
S Albaradei, MA Thafar, C Van Neste, M Essack, VB Bajic
Proceedings of the 2019 6th International Conference on Bioinformatics …, 2019
Computational Drug-target Interaction Prediction based on Graph Embedding and Graph Mining
MA Thafar, S Albaradei, RS Olayan, H Ashoor, M Essack, VB Bajic
10th International Conference on Bioscience, Biochemistry and Bioinformatics …, 2020
A Formal Approach for Multimodal Integration to Derive Emotions
M Ghayoumi, MA Thafar, AK Bansal
Journal of Visual Languages and Sentient Systems, 48-54, 2016
Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models
S Albaradei, M Uludag, MA Thafar, T Gojobori, M Essack, X Gao
Frontiers in genetics, 2217, 2021
An Abstract Model of Multimodal Fusion Using Fuzzy Sets to Derive Interactive Emotions
MA Thafar, AK Bansal
International Conference of Artificial Intelligence, Las Vegas, 2016
Identification of the ubiquitin–proteasome pathway domain by hyperparameter optimization based on a 2D convolutional neural network
R Sikander, M Arif, A Ghulam, A Worachartcheewan, MA Thafar, S Habib
Frontiers in Genetics 13, 851688, 2022
VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants
F Ge, C Li, S Iqbal, A Muhammad, F Li, MA Thafar, Z Yan, ...
Briefings in Bioinformatics 24 (1), bbac535, 2023
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Artikkelit 1–20