Muhammad Kabir
PhD Computer Science and Technology
About Me
Hello (اَلسَّلَامُ عَلَيْكُم)! My name is Muhammad Kabir and I am thrilled to introduce myself as a postdoctoral researcher in the field of Bioinformatics. I received my bachelor’s degree in computer science from Islamia College Peshawar, in 2012, and the master’s degree in Computer Science from Abdul Wali Khan University Mardan, Pakistan, in 2016. I completed my PhD degree in Computer Science and Technology from the School of Computer Science and Engineering, Nanjing University of Science and Technology (NJUST), Nanjing, China. I served as an Assistant Professor at the School of Systems and Technology - Department of Computer Science, University of Management and Technology (UMT), Lahore, Pakistan for 2.5 years. Currently, I am working as a researcher in the Protein Structure and Bioinformatics Group, Biomedical Center (BMC), Lund University, Sweden. I am keen on immersing myself in a stimulating research environment, aiming to enhance my existing skills while acquiring new ones to remain current in the dynamic field of bioinformatics. In my current postdoctoral research, I am dedicated to advancing machine learning methods specifically tailored for the identification and classification of disease-causing genetic variations, with the ultimate goal of contributing to both research and clinical applications.
Bio
mdkabircs@gmail.com
Urdu (National Language)
Pashto (Mother tongue)
Work Experience
Education
Research Interest
Research Publications
Sameera Kanwal, Roha Arif, Saeed Ahmed and Muhammad Kabir*: A novel stacking-based predictor for accurate prediction of antimicrobial peptides. [J] Journal of Biomolecular Structure and Dynamics . 2024, https://doi.org/10.1080/07391102.2024.2329298.
Farwa Arshad, Saeed Ahmed, Aqsa Amjad and Muhammad Kabir*: A stacking-based approach for accurate prediction of antidiabetic peptides. [J] Analytical Biochemistry . 2024, https://doi.org/10.1016/j.ab.2024.115546.
Roha Arif, Sameera Kanwal, Saeed Ahmed and Muhammad Kabir*: A novel predictor for accurate identification of tumor homing peptides by integrating sequential and deep BiLSTM features. [J] Interdisciplinary Sciences: Computational Life Sciences. . 2024, (ONLINE SOON).
Mehwish Gill, Muhammad Kabir*, Saeed Ahmad, MA Subhani, Maqsood Hayat; Large-scale analysis and comparative review of computational predictors for identification of enhancers and their strength. [J] Current Bioinformatics . 2024, (ONLINE SOON).
Mehwish Gill, Saeed Ahmad, Muhammad Kabir*, Maqsood Hayat; A Novel Predictor for the Analysis and Prediction of Enhancers and Their Strength via Multi-View Features and Deep Forest. [J] Information - MDPI , 2023, 14(12), 636
Muhammad Arif, Muhammad Kabir , Saeed Ahmad, Abid Khan, Fang Ge, Adel Khelifi, Dong-Jun Yu DeepCPPred: a deep learning framework for the discrimination of cell-penetrating peptides and their uptake efficiencies. [J] IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2022, 19(5), page(s) 2749-2759.
Muhammad Kabir, Muhammad Kabir, Chanin Nantasenamat, Sakawrat Kanthawong, Phasit Charoenkwan, Watshara Shoombuatong*; Large-scale comparative review and assessment of computational methods for phage virion proteins identification. [J] Excli Journal . 2022, 11-29
Saeed Ahmed, Muhammad Arif, Muhammad Kabir*, Khaistah Khan, Yaser Daanial Khan; PredAoDP: Accurate identification of antioxidant proteins by fusing different descriptors based on evolutionary information with support vector machine. [J] Chemometrics and Intelligent Laboratory Systems . 2022, 228 - 104623
Muhammad Arif, Saeed Ahmad, Fang Ge, Muhammad Kabir*, Yaser Daniaal Khan, Dong-Jun Yu*, Maha Thafar; StackACPred: Prediction of anticancer peptides by integrating optimized multiple feature descriptors with stacked ensemble approach. [J] Chemometrics and Intelligent Laboratory Systems . 2022, 220 - 104458
Saeed Ahmad, Muhammad Kabir, Muhammad Arif, Zaheer Ullah Khan, Dong-Jun Yu*; DeepPPSite: A deep learning based model for analysis and prediction of phosphorylation sites using efficient sequence information. [J] Analytical Biochemistry. 2021, 612, 113955.
Saeed Ahmad, Muhammad Kabir*, Muhammad Arif, Zakir Ali, Zar Nawab Khan Swati; Prediction of human phosphorylated proteins by extracting multi-perspective discriminative features from the evolutionary profile and physicochemical properties through LFDA. [J] Chemometrics and Intelligent Laboratory Systems. 2020, 203, 104066.
Muhammad Arif, Farman Ali, Saeed Ahmad, Muhammad Kabir, Zakir Ali, Maqsood Hayat*; Pred-BVP-Unb: Fast Prediction of Bacteriophage Virion Proteins Using Un-biased Multi-perspective Properties with Recursive Feature Elimination. [J] Genomics. 2020, 112(2):1565-1574.
Muhammad Kabir*, Muhammad Iqbal, Saeed Ahmad, Maqsood Hayat*; iNR-2L: A two-level sequence-based predictor developed via Chou’s 5-steps rule and general PseAAC for identifying nuclear receptors and their families. [J] Genomics. 2020, 112(1):276-285.
Farman Ali, Muhammad Arif, Zaheer Ullah Khan, Muhammad Kabir, Saeed Ahmad, Dong-Jun Yu*; SDBP-Pred: Prediction of single-stranded and double-stranded DNA-binding proteins by extending consensus sequence and K-segmentation strategies into PSSM. [J] Analytical Biochemistry. 2020, 589:113494.
Zar Nawab Khan Swati, Qinghua Zhao, Muhammad Kabir, Farman Ali, Zakir Ali, Saeed Ahmad, Jianfeng Lu*; Brain Tumor Classification for MR Images using Transfer Learning and Fine-Tuning. [J] Computerized Medical Imaging and Graphics. 2019, 75:34-46.
Shahid Akbar, Maqsood Hayat*, Muhammad Kabir, Muhammad Iqbal; iAFP-gap-SMOTE: An efficient feature extraction scheme gapped dipeptide composition is coupled with oversampling technique for Identification of Antifreeze proteins. [J] Letters in Organic Chemistry. 2019, 16(4), 294-302.
Zar Nawab Khan Swati, Qinghua Zhao, Muhammad Kabir, Farman Ali, Zakir Ali, Saeed Ahmad, Jianfeng Lu*; Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning. [J] IEEE Access. 2019, 7(1):17809-17822.
Muhammad Kabir, Muhammad Arif, Farman Ali, Saeed Ahmad, Zar Nawab Khan Swati, Dong-Jun Yu*; Prediction of membrane protein types by exploring local discriminative information from evolutionary profiles. [J] Analytical Biochemistry. 2019, 564-565:123-132.
Saeed Ahmad*, Muhammad Kabir, Zakir Ali, Muhammad Arif, Farman Ali, Dong-Jun Yu; An Integrated Feature Selection algorithm for Cancer Classification using Gene Expression Data. [J] Combinatorial Chemistry & High Throughput Screening. 2018, 21(9):631-645.
Saeed Ahmad*, Muhammad Kabir*, Muhammad Arif, Zakir Ali, Farman Ali, Zar Nawab Khan Swati; Improving secretory proteins prediction in Mycobacterium tuberculosis using the unbiased dipeptide composition with support vector machine. [J] International Journal of Data Mining and Bioinformatics. 2018,21(3):212-229.
Muhammad Kabir, Muhammad Arif, Saeed Ahmad, Zakir Ali, Zar Nawab Khan Swati, Dong-Jun Yu*; Intelligent computational method for discrimination of anticancer peptides by incorporating sequential and evolutionary profiles information. [J] Chemometrics and Intelligent Laboratory Systems . 2018, 182:158-165.
Farman Ali, Muhammad Kabir, Muhammad Arif, Zar Nawab Khan Swati, Zaheer Ullah Khan, Matee Ullah, Dong-Jun Yu*; DBPPred-PDSD: Machine Learning Approach for Prediction of DNA-binding Proteins using Discrete Wavelet Transform and Optimized Integrated Features Space. [J] Chemometrics and Intelligent Laboratory Systems. 2018, 182; 21-30.
Muhammad Kabir, Saeed Ahmad, Muhammad Iqbal, Zar Nawab Khan Swati, Zi Liu, Dong-Jun Yu*; Improving prediction of extracellular matrix proteins using evolutionary information via a grey system model and asymmetric under-sampling technique. [J] Chemometrics and Intelligent Laboratory Systems. 2018, 174; 22-32.
Muhammad Kabir, Dong-Jun Yu*; Predicting DNase I Hypersensitive sites via un-biased Pseudo Trinucleotide Composition. [J] Chemometrics and Intelligent Laboratory Systems. 2017, 167: 78-84.
Muhammad Tahir, Maqsood Hayat*, Muhammad Kabir; Sequence based predictor for discrimination of Enhancer and their Types by applying general form of Chou's Trinucleotide Composition. [J] Computer Methods and Programs in Biomedicine . 2017, 146: 69-75.
Muhammad Waris, Khurshid Ahmad, Muhammad Kabir, Maqsood Hayat*; Identification of DNA binding proteins using evolutionary profiles position specific scoring matrix. [J] Neurocomputing . 2016, 199: 154-162.
Muhammad Kabir, Maqsood Hayat*; iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou's PseAAC to formulate DNA samples. [J] Molecular Genetics and Genomics . 2016, 291 (1): 285-296.
Muhammad Kabir, Muhammad Iqbal, Saeed Ahmad, Maqsood Hayat*; iTIS-PseKNC: Identification of Translation Initiation Site in human genes using pseudo k-tuple nucleotides composition. [J] Computers in Biology and Medicine. 2015, 66: 252-257.
Saeed Ahmad, Muhammad Kabir, Maqsood Hayat*; Identification of Heat Shock Protein Families and J-Protein Types by incorporating Dipeptide Composition into Chou's general PseAAC. [J] Computer Methods and Programs in Biomedicine. 2015, 122: 165-174.
Students Supervised
Editorial and Reviewer Services
Guest Editoror for Special Issue " Applications of Deep Learning in Bioinformatics and Image Processing" Information Journal MDPI – On going issue.
Member of Editorial Board in journal "BMC Bioinformatics", BMC Part of Springer Nature"
Member of Editorial Board in journal "Innovative Medicines & Omics (IMO)", ACCSciene Publishers."
Member of Editorial Board in journal "Innovative Computing Review (ICR)", managed by UMT.
- Briefings in Bioinformatics.
- Engineering Applications of Artificial Intelligence.
- Current Opinion in Biomedical Engineering.
- Artificial Intelligence In Medicine.
- Journal of Computational Biology.
- Computers in Biology and Medicine.
- Knowledge-Based Systems.
- Information Science.
- Genomics.
- ACS Omega.
- SN Applied Sciences.
- SAR and QSAR in Environmental Research.
- IEEE Journal of Biomedical and Health Informatics.
- Visual Computing for Industry, Biomedicine, and Art.
- Journal of King Saud University - Computer and Information Sciences.
- IEEE Access.
- AI Open.
- Genes - MDPI.
- Symmetry - MDPI.
- International Conference on Innovative Computing – UMT.
- International Conference on Frontiers of Information Technology - COMSATS.
References
Mauno Vihinen
Professor at Lund University
Professor Mauno Vihinen is well-known for his experience and interest in investigating variations and their effects whether they emerge at molecular levels (DNA, RNA protein), in structural context or in the cellular networks and pathways. He has published numerous original ideas and reports, established standards and guidelines for variations and variation databases and developed tools and performed analyses for the interpretation of variations in several diseases. The major part of his production relates to variations ranging from protein engineering to effects and mechanisms of variations in protein structures, genes and diseases.
Maqsood Hayat
Professor at Abdul Wali Khan University Mardan
Professor Maqsood Hayat is an eminent researcher in the field of Bioinformatics, pattern recognition and image processing. He has published more than 50 papers in different aspects of his fields of interests. His research interests lies in the interface of statistical machine learning, pattern recognition, Evolutionary computing and some emerging data-rich areas such as computational biology and bioinformatics. He has a demonstrated history of working in the higher education industry. Skilled in Research, Matlab, Computer Vision, C, and C++. Strong research professional with a focused in Information retreival and processing.