Muhammad Shahid Malik

Muhammad Shahid Malik

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Email: shahidmalik@kiu.edu.pk

Muhammad Shahid Malik holds a Ph.D. in Computer Science and Engineering with a specialization in Bioinformatics and Computational Biology from Yuan Ze University, Taiwan. His research focuses on developing deep learning-based methods to analyze biological sequences, predict molecular interactions, and develop drugs using artificial intelligence. He is also engaged in the Deep Volume Editing project in the field of image processing in addition to his work in bioinformatics.

  • B.Sc (math,state,Computer Science) University of Karachi
  • MCS University of Karachi
  • MS(CS) COMSATS Institute of Information Technology, Islamabad
  • Ph.D. Yuan Ze University, Chung-Li, 32003, Taiwan
  • Lecturer Karakoram International University
  • Data & Network Administrator Telenor

  • Taiwan Government Elite Scholarship Awardee; Pursuing PhD at Yuan Ze University

  • Image Processing
  • Algorithms Analysis

  •  Specializing in bioinformatics and computational biology  Integrating machine learning and deep learning techniques  Analyzing biological data such as genomic sequences and protein structures  Applying computational methods to gain insights into biological processes  Research focus includes natural language processing for biomedical literature analysis

    • The challenges and opportunities to formulate and integrate an effective ict policy at mountainous rural schools of gilgit-baltistan, Sabit Rahim, Tehmina Bibi, Sadruddin Bahadur Qutoshi, Shehla Gul, Yasmeen Gul, Naveed Ali Khan Kaim Khani, Muhammad Shahid Malik: Information:MDPI
    • AOPs-XGBoost: Machine learning Model for the prediction of Antioxidant Proteins properties of peptides, Sikander Rahu, Ali Ghulam, Zar Nawab Khan Swati, Jawad Usman Arshed, Muhammad Shahid Malik : VAWKUM Transactions on Computer Sciences
    • XGboost-Ampy: Identification of AMPylation Protein Function Prediction Using Machine Learning, XGboost-Ampy: Identification of AMPylation Protein Function Prediction Using Machine Learning : VAWKUM Transactions on Computer Sciences
    • Integrating Pre-Trained protein language model and multiple window scanning deep learning networks for accurate identification of secondary active transporters in membrane proteins, Muhammad Shahid Malik, Yu-Yen Ou : Methods: Academic Press
    • DeepPLM_mCNN: An approach for enhancing Ion Channel and Ion Transporter Recognition by Multi-Window CNN based on features from Pre-trained Language Models, Van-The Le, Muhammad-Shahid Malik, Yi-Hsuan Tseng, Yu-Cheng Lee, Cheng-I Huang, Yu-Yen Ou : Computational Biology and Chemistry : Elsevier
    • ProtTrans and Multi-Window Scanning Convolutional Neural Networks for the Prediction of Protein-Peptide Interaction Sites, Van-The Le 1, Zi-Jun Zhan , Thi-Thu-Phuong Vu , Muhammad-Shahid Malik , Yu-Yen Ou : Journal of Molecular Graphics and Modelling :ELSEVIER /2024
    • MCNN_MC: Computational Prediction of Mitochondrial Carriers and Investigation of Bongkrekic Acid Toxicity Using Protein Language Models and Convolutional Neural Networks, Muhammad Shahid Malik, Yan-Yun Chang, Yu-Chen Liu, Van The Le, and Yu-Yen Ou
    • VesiMCNN: Using pre-trained protein language models and multiple window scanning convolutional neural networks to identify vesicular transport proteins, International Journal of Biological Macromolecules
    • MCNN-AAPT: accurate classification and functional prediction of amino acid and peptide transporters in secondary active transporters using protein language models and multi-window deep learning, Muhammad Shahid Malik, Van The Le, Syed Muazzam Ali Shah & Yu-Yen Ou
    • ATP_mCNN: Predicting ATP binding sites through pretrained language models and multi-window neural networks, Van-The Le, Muhammad-Shahid Malik, Yi-Jing Lin, Yu-Chen Liu, Yan-Yun Chang, Yu-Yen Ou
    • mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows, Syed Muazzam Ali Shah, Muhammad Rafi, Muhammad Shahid Malik, Sohail Ahmed Malik, Yu-Yen Ou
    • NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction, Van‐The Le, Yu‐Chen Liu, Yan‐Yun Chang, Yu‐Cheng Lee, Yi‐Jing Lin, Muhammad‐Shahid Malik, Yu‐Yen Ou
    • NA_mCNN: Classification of Sodium Transporters in Membrane Proteins by Integrating Multi-Window Deep Learning and ProtTrans for Their Therapeutic Potential, Muhammad Shahid Malik, Van The Le, Yu-Yen Ou
    • DeepCR: predicting cytokine receptor proteins through pretrained language models and deep learning networks, Journal of Biomolecular Structure and Dynamics
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