• Prof. Dr. Maqsood Hayat

  • Experience

    Designation Service Type From To
    Professor TTS Feb 8, 2023 August 24 2025
    Associate Professor TTS Aug 15, 2018 Feb 7, 2023
    Assistant Professor TTS Aug 15, 2012 Aug 14, 2018

  • Biblography

  • Research Publications

    S.No: Title
    1 Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition
    2 MemHyb: Predicting membrane protein types by hybridizing SAAC and PSSM
    3 Prediction of membrane proteins using split amino acid and ensemble classification
    4 Prediction of membrane protein types by using dipeptide and pseudo amino acid composition-based composite features
    5 CE-PLoc: An ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition
    6 Mem-PHybrid: Hybrid features-based prediction system for classifying membrane protein types
    7 Discriminating Outer Membrane Proteins with Fuzzy K-Nearest Neighbor Algorithms Based on the General Form of Chou’s PseAAC
    8 WRF-TMH: predicting transmembrane helix by fusing composition index and physicochemical properties of amino acids
    9 Discriminating protein structure classes by incorporating Pseudo Average Chemical Shift to Chou’s general PseAAC and Support Vector Machine
    10 Prediction of protein structure classes using hybrid space of multi-profile Bayes and bi-gram probability feature spaces
    11 Discrimination of acidic and alkaline enzyme using Chou’s pseudo amino acid composition in conjunction with probabilistic neural network model
    12 iTIS-PseKNC: Identification of Translation Initiation Site in human genes using pseudo k-tuple nucleotides composition
    13 Identification of Heat Shock Protein families and J-protein types by incorporating Dipeptide Composition into Chou’s general PseAAC
    14 PSOFuzzySVM-TMH: identification of transmembrane helix segments using ensemble feature space by incorporated fuzzy support vector machine
    15 Classification of membrane protein types using Voting Feature Interval in combination with Chou's Pseudo Amino Acid Composition
    16 “iSS-Hyb-mRMR”: Identification of splicing sites using hybrid space of pseudo trinucleotide and pseudo tetranucleotide composition
    17 Prediction of Protein Submitochondrial Locations by Incorporating Dipeptide Composition into Chou’s General Pseudo Amino Acid Composition
    18 iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou’s PseAAC to formulate DNA samples
    19 iNuc-STNC: a sequence-based predictor for identification of nucleosome positioning in genomes by extending the concept of SAAC and Chou’s PseAAC
    20 Identification of DNA binding proteins using evolutionary profiles position specific scoring matrix
    21 Machine learning approaches for discrimination of Extracellular Matrix proteins using hybrid feature space
    22 Intelligent computational model for classification of sub-Golgi protein using oversampling and fisher feature selection methods
    23 iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space
    24 Machine learning based identification of protein–protein interactions using derived features of physiochemical properties and evolutionary profiles
    25 A Two-Layer Computational Model for Discrimination of Enhancer and Their Types Using Hybrid Features Pace of Pseudo K-Tuple Nucleotide Composition
    26 Sequence based predictor for discrimination of enhancer and their types by applying general form of Chou’s trinucleotide composition
    27 Bi-PSSM: Position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins
    28 Unb-DPC: Identify mycobacterial membrane protein types by incorporating un-biased dipeptide composition into Chou's general PseAAC
    29 iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou’s pseudo amino acid composition
    30 Efficient computational model for classification of protein localization images using Extended Threshold Adjacency Statistics and Support Vector Machines
    31 iNuc-ext-PseTNC: an efficient ensemble model for identification of nucleosome positioning by extending the concept of Chou’s PseAAC to pseudo-tri-nucleotide composition
    32 iMem-2LSAAC: A two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into chou's pseudo amino acid composition
    33 Predicting subcellular localization of multi-label proteins by incorporating the sequence features into Chou's PseAAC
    34 iAFP-gap-SMOTE: an efficient feature extraction scheme gapped dipeptide composition is coupled with an oversampling technique for identification of antifreeze proteins
    35 MFSC: Multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou's PseAAC components
    36 iPredCNC: Computational prediction model for cancerlectins and non-cancerlectins using novel cascade features subset selection
    37 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
    38 cACP: Classifying anticancer peptides using discriminative intelligent model via Chou’s 5-step rules and general pseudo components
    39 Pred-BVP-Unb: Fast prediction of bacteriophage Virion proteins using un-biased multi-perspective properties with recursive feature elimination
    40 iRNA-PseTNC: identification of RNA 5-methylcytosine sites using hybrid vector space of pseudo nucleotide composition
    41 An intelligent computational model for prediction of promoters and their strength via natural language processing
    42 ML-RBF: Predict protein subcellular locations in a multi-label system using evolutionary features
    43 Prediction of N6-methyladenosine sites using convolution neural network model based on distributed feature representations
    44 cACP-2LFS: Classification of Anticancer Peptides Using Sequential Discriminative Model of KSAAP and Two-Level Feature Selection Approach
    45 iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach
    46 Early and accurate detection and diagnosis of heart disease using intelligent computational model
    47 A deep learning-based computational approach for discrimination of DNA N6-methyladenosine sites by fusing heterogeneous features
    48 Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks
    49 kDeepBind: Prediction of RNA-Proteins binding sites using convolution neural network and k-gram features

  • Awards

    Organization Description Date
    Pakistan Council for Science and Technology Research Productivity Award for the year 2017 "Category -A" Apr 12, 2017
    Pakistan Council for Science and Technology Research Productivity Award for the year 2016 "Category -D" Apr 15, 2016
    Abdul Wali Khan University Mardan Best Researcher Award Nov 13, 2015
    Higher Education Commission Best Paper HEC outstanding Award for the year 2013 Jun 21, 2014
    Pakistan Council for Science and Technology Research Productivity Award for the year 2013"Category -C" Apr 16, 2014
    Pakistan Council for Science and Technology Research Productivity Award for the year 2012 "Category -G" Apr 16, 2013
    IEEE 6th IEEE International Conference on Emerging Technology (ICET, 2010) Fast, Islamabad Nov 13, 2011
    Higher Education Commission Six months IRSIP scholarship for University of Illinois, Urbana Champaign, Illinois, USA Aug 5, 2011
    Higher Education Commission HEC indigenous PhD scholarship batch-II Feb 1, 2007

  • Conferences

    Level Country City Conference Dated
    National Pakistan Islamabad 6th IEEE International Conference on Emerging Technologies, (ICET 2010) Oct 21, 2010
    International Turky Rize 2nd International Conference on Computational and Social Sciences (ICCSS-14) Aug 26, 2014

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