A. Dehzangi

发表

Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳s general PseAAC.

James G. Lyons, K. Paliwal, A. Dehzangi, 2015, Journal of theoretical biology.

Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction

T. Tsunoda, A. Dehzangi, Alok Sharma, 2018, BMC Genomics.

CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering.

Javad Hassannataj Joloudari, M. Sookhak, Sadiq Hussain, 2022, Mathematical biosciences and engineering : MBE.

Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning

James G. Lyons, K. Paliwal, Yaoqi Zhou, 2015, Scientific Reports.

PhoglyStruct: Prediction of phosphoglycerylated lysine residues using structural properties of amino acids

S. Ranganathan, T. Tsunoda, K. Chou, 2018, Scientific Reports.

PupStruct: Prediction of Pupylated Lysine Residues Using Structural Properties of Amino Acids

A. Dehzangi, Alok Sharma, Vineet Singh, 2020, Genes.

CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data

Khondaker Abdullah Al Mamun, Md. Ochiuddin Miah, K. Mamun, 2021, Journal of Neuroscience Methods.

CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data

Md. Ochiuddin Miah, K. Mamun, A. Dehzangi, 2021, Journal of Neuroscience Methods.

PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction.

T. Tsunoda, J. Michaelson, A. Dehzangi, 2017, Journal of theoretical biology.

SucStruct: Prediction of succinylated lysine residues by using structural properties of amino acids.

T. Tsunoda, J. Michaelson, A. Dehzangi, 2017, Analytical biochemistry.

Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix

T. Tsunoda, A. Dehzangi, Alok Sharma, 2019, BMC Molecular and Cell Biology.

Predict Gram-Positive and Gram-Negative Subcellular Localization via Incorporating Evolutionary Information and Physicochemical Features Into Chou's General PseAAC

James G. Lyons, K. Paliwal, T. Tsunoda, 2015, IEEE Transactions on NanoBioscience.

EvolStruct-Phogly: incorporating structural properties and evolutionary information from profile bigrams for the phosphoglycerylation prediction

A. Dehzangi, Alok Sharma, A. Chandra, 2019, BMC Genomics.

SumSec: Accurate Prediction of Sumoylation Sites Using Predicted Secondary Structure

T. Tsunoda, A. Dehzangi, Alok Sharma, 2018, Molecules.

Probabilistic expression of spatially varied amino acid dimers into general form of Chou׳s pseudo amino acid composition for protein fold recognition.

James G. Lyons, K. Paliwal, S. Miyano, 2015, Journal of theoretical biology.

HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acids residues

T. Tsunoda, A. Dehzangi, Alok Sharma, 2019, BMC Genomics.

Chapter 6 SPIDER 2 : A Package to Predict Secondary Structure , Accessible Surface Area , and Main-Chain Torsional Angles by Deep Neural Networks

James G. Lyons, K. Paliwal, Yaoqi Zhou, 2016 .

REDICTING THE S ECONDARY S TRUCTURE OF P ROTEINS BY C ASCADING N EURAL N ETWORKS

A. Dehzangi, E. Mansoori, M. Alirezaee, 2012 .

IMBALANCE PROBLEM OF P ROTEIN S ECONDARY S TRUCTURE P REDICTION

A. Dehzangi, E. Mansoori, M. Alirezaee, 2012 .

Integrative analysis of mutated genes and mutational processes reveals seven colorectal cancer subtypes

Nigel H. Lovell, N. Lovell, H. Rabiee, 2020, bioRxiv.

SPIN 2 : Predicting sequence profiles from protein structures using deep neural networks

James G. Lyons, K. Paliwal, Yaoqi Zhou, 2018 .

Quantitative Toxicity Prediction via Ensembling of Heterogeneous Predictors

M. A. Hakim Newton, A. Sattar, A. Dehzangi, 2019 .

An Investigation of Point Mutations Discovers Novel Genes and Their Corresponding Motifs in Pancreatic Cancer

H. Rabiee, A. Dehzangi, H. Dashti, 2021 .

EXPLORING TECHNIQUES FOR OPTIMAL FEATURE AND CLASSIFIER SELECTION FOR PROTEIN MODELING, FUNCTION, AND FOLD RECOGNITION

James G. Lyons, K. Paliwal, S. Miyano, 2015 .

CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering.

Roohallah Alizadehsani, Hamid Alinejad-Rokny, Shahab Shamshirband, 2020, Mathematical biosciences and engineering : MBE.

CovidMulti-Net: A Parallel-Dilated Multi Scale Feature Fusion Architecture for the Identification of COVID-19 Cases from Chest X-ray Images

Shahab S. Band, M. I. Khan, Md. Razaul Karim, 2021, medRxiv.

Proposing a novel community detection approach to identify cointeracting genomic regions.

Abdollah Dehzangi, Hamid Parvin, Samad Nejatian, 2020, Mathematical biosciences and engineering : MBE.

A strategy to select suitable physicochemical attributes of amino acids for protein fold recognition

Kuldip K. Paliwal, Satoru Miyano, James G. Lyons, 2013, BMC Bioinformatics.

Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2016, Bioinform..

SPRINT-Gly: predicting N- and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties

Abdollah Dehzangi, Yaoqi Zhou, Matthew P Campbell, 2019, Bioinform..

PyFeat: a Python-based effective feature generation tool for DNA, RNA and protein sequences

Abdollah Dehzangi, Sajid Ahmed, Swakkhar Shatabda, 2019, Bioinform..

SPIN2: Predicting sequence profiles from protein structures using deep neural networks

James G. Lyons, Abdollah Dehzangi, Rhys Heffernan, 2018, Proteins.

Enhancing Protein Fold Prediction Accuracy Using an Ensemble of Different Classifiers

Somnuk Phon-Amnuaisuk, Abdollah Dehzangi, Omid Dehzangi, 2009, Aust. J. Intell. Inf. Process. Syst..

Enhancing protein backbone angle prediction by using simpler models of deep neural networks

Abdollah Dehzangi, M. A. Hakim Newton, Shoba Ranganathan, 2020, Scientific Reports.

Whole-Genome Analysis of De Novo Somatic Point Mutations Reveals Novel Mutational Biomarkers in Pancreatic Cancer

A. Beheshti, H. Rabiee, A. Dehzangi, 2021, Cancers.

VIRMOTIF: A User-Friendly Tool for Viral Sequence Analysis

A. Beheshti, A. Dehzangi, Khadijeh Jahanian, 2021, Genes.

A novel one-class classification approach to accurately predict disease-gene association in acute myeloid leukemia cancer

Abdollah Dehzangi, Alok Sharma, Akram Vasighizaker, 2019, PloS one.

Protein Fold Recognition Using Genetic Algorithm Optimized Voting Scheme and Profile Bigram

Abdollah Dehzangi, Alok Sharma, Sunil Pranit Lal, 2016, J. Softw..

Exploring Potential Discriminatory Information Embedded in PSSM to Enhance Protein Structural Class Prediction Accuracy

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2013, PRIB.

GlyStruct: glycation prediction using structural properties of amino acid residues

Abdollah Dehzangi, Alok Sharma, Daichi Shigemizu, 2019, BMC Bioinformatics.

iProtGly‐SS: Identifying protein glycation sites using sequence and structure based features

Abdollah Dehzangi, Swakkhar Shatabda, Md. Mofijul Islam, 2018, Proteins.

SEMal: Accurate protein malonylation site predictor using structural and evolutionary information

Abdollah Dehzangi, Swakkhar Shatabda, Shubhashis Roy Dipta, 2020, Comput. Biol. Medicine.

Accurate prediction of RNA 5-hydroxymethylcytosine modification by utilizing novel position-specific gapped k-mer descriptors

Sajid Ahmed, Swakkhar Shatabda, Abdollah Dehzangi, 2020, Computational and structural biotechnology journal.

SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks.

James G. Lyons, Abdollah Dehzangi, Rhys Heffernan, 2017, Methods in molecular biology.

A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues

Anthony T. Chronopoulos, Abdollah Dehzangi, Shahab Shamshirband, 2020, J. Biomed. Informatics.

Proposing a highly accurate protein structural class predictor using segmentation-based features

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2014, BMC Genomics.

A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition.

James G. Lyons, Abdollah Dehzangi, Alok Sharma, 2013, Journal of theoretical biology.

RAM-PGK: Prediction of Lysine Phosphoglycerylation Based on Residue Adjacency Matrix

A. Dehzangi, Alok Sharma, A. Chandra, 2020, Genes.

ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides

Swakkhar Shatabda, A. Dehzangi, Alok Sharma, 2020, Scientific Reports.

Gram-positive and gram-negative subcellular localization using rotation forest and physicochemical-based features

Kuldip K. Paliwal, James G. Lyons, Rhys Heffernan, 2015, BMC Bioinformatics.

Enhancing the Performance of a Model to Predict Driving Distraction with the Random Forest Classifier

Abdollah Dehzangi, Mansoureh Jeihani, Samira Ahangari, 2021, Transportation Research Record: Journal of the Transportation Research Board.

EvoStruct-Sub: An accurate Gram-positive protein subcellular localization predictor using evolutionary and structural features.

Abdollah Dehzangi, Alok Sharma, Swakkhar Shatabda, 2018, Journal of theoretical biology.

Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams

Abdollah Dehzangi, Alok Sharma, Yosvany López, 2018, PloS one.

iPHLoc-ES: Identification of bacteriophage protein locations using evolutionary and structural features.

Abdollah Dehzangi, Swakkhar Shatabda, Sanjay Saha, 2017, Journal of theoretical biology.

HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features

Abdollah Dehzangi, Alok Sharma, Mahmood A. Rashid, 2017, BioMed research international.

iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features

Abdollah Dehzangi, Swakkhar Shatabda, Shahana Yasmin Chowdhury, 2017, Scientific Reports.

Protein fold recognition using HMM-HMM alignment and dynamic programming.

James G. Lyons, Abdollah Dehzangi, Rhys Heffernan, 2016, Journal of theoretical biology.

Subcellular localization for Gram positive and Gram negative bacterial proteins using linear interpolation smoothing model.

Abdollah Dehzangi, Alok Sharma, Sunil Lal, 2015, Journal of theoretical biology.

Importance of dimensionality reduction in protein fold recognition

Ronesh Sharma, James G. Lyons, Abdollah Dehzangi, 2015, 2015 2nd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE).

A mixture of physicochemical and evolutionary-based feature extraction approaches for protein fold recognition

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2015, Int. J. Data Min. Bioinform..

Protein Fold Recognition Using an Overlapping Segmentation Approach and a Mixture of Feature Extraction Models

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2013, Australasian Conference on Artificial Intelligence.

Enhancing Protein Fold Prediction Accuracy Using Evolutionary and Structural Features

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2013, PRIB.

A Combination of Feature Extraction Methods with an Ensemble of Different Classifiers for Protein Structural Class Prediction Problem

Abdollah Dehzangi, Alok Sharma, Abdul Sattar, 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Ensemble of Diversely Trained Support Vector Machines for Protein Fold Recognition

Abdollah Dehzangi, Abdul Sattar, A. Sattar, 2013, ACIIDS.

Protein Fold Recognition Using Segmentation-Based Feature Extraction Model

Abdollah Dehzangi, Abdul Sattar, A. Sattar, 2013, ACIIDS.

Fold prediction problem: the application of new physical and physicochemical-based features.

Abdollah Dehzangi, Somnuk Phon-Amnuaisuk, S. Phon-Amnuaisuk, 2011, Protein and peptide letters.

Solving protein fold prediction problem using fusion of heterogeneous classifiers

Abdollah Dehzangi, Abdollah Dehzangi, Sasan Karamizadeh, 2011 .

Using Rotation Forest for Protein Fold Prediction Problem: An Empirical Study

Somnuk Phon-Amnuaisuk, Abdollah Dehzangi, Soodabeh Safa, 2010, EvoBIO.

Protein Fold Prediction Problem Using Ensemble of Classifiers

Somnuk Phon-Amnuaisuk, Abdollah Dehzangi, Keng Hoong Ng, 2009, ICONIP.

Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

Abdollah Dehzangi, Alok Sharma, Sunil Lal, 2016, Journal of theoretical biology.

Computer-aided decision-making for predicting liver disease using PSO-based optimized SVM with feature selection

Shahaboddin Shamshirband, Abdollah Dehzangi, Javad Hassannataj Joloudari, 2019, Informatics in Medicine Unlocked.

Quantitative Toxicity Prediction via Meta Ensembling of Multitask Deep Learning Models

M. A. Hakim Newton, A. Dehzangi, Abdul Sattar, 2021, ACS omega.

Toxicity Prediction by Multimodal Deep Learning

Abdul Sattar, M. A. Hakim Newton, Abdul Karim, 2019, PKAW.

Improving protein fold recognition using the amalgamation of evolutionary-based and structural based information

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2014, BMC Bioinformatics.

Protein fold recognition by alignment of amino acid residues using kernelized dynamic time warping.

James G. Lyons, Abdollah Dehzangi, Alok Sharma, 2014, Journal of theoretical biology.

Protein Structural Class Prediction via k-Separated Bigrams Using Position Specific Scoring Matrix

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2014, J. Adv. Comput. Intell. Intell. Informatics.

A Tri-Gram Based Feature Extraction Technique Using Linear Probabilities of Position Specific Scoring Matrix for Protein Fold Recognition

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2014, IEEE Transactions on NanoBioscience.

GlyStruct: glycation prediction using structural properties of amino acid residues

A. Dehzangi, Alok Sharma, A. Chandra, 2019, BMC Bioinformatics.

Mal-Light: Enhancing Lysine Malonylation Sites Prediction Problem Using Evolutionary-based Features

Abdollah Dehzangi, Swakkhar Shatabda, Shubhashis Roy Dipta, 2020, IEEE Access.

iDNAProt-ES: Identification of DNA-binding Proteins Using Evolutionary and Structural Features

Shahana Yasmin Chowdhury, Swakkhar Shatabda, A. Dehzangi, 2017, Scientific Reports.

iDTI-ESBoost: Identification of Drug Target Interaction Using Evolutionary and Structural Features with Boosting

Abdollah Dehzangi, Mohammad Sohel Rahman, Sajid Ahmed, 2017, Scientific Reports.

PhoglyStruct: Prediction of phosphoglycerylated lysine residues using structural properties of amino acids

S. Ranganathan, T. Tsunoda, K. Chou, 2018, Scientific Reports.

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network

Kuldip K. Paliwal, James G. Lyons, Abdollah Dehzangi, 2014, J. Comput. Chem..

A Machine Learning Distracted Driving Prediction Model

Abdollah Dehzangi, Mansoureh Jeihani, Samira Ahangari, 2019, ICVISP.

Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction

T. Tsunoda, A. Dehzangi, Alok Sharma, 2018, BMC Genomics.

HseSUMO: Sumoylation site prediction using half-sphere exposures of amino acids residues

T. Tsunoda, A. Dehzangi, Alok Sharma, 2019, BMC Genomics.

Advancing the Accuracy of Protein Fold Recognition by Utilizing Profiles From Hidden Markov Models

James G. Lyons, Abdollah Dehzangi, Rhys Heffernan, 2015, IEEE Transactions on NanoBioscience.

Accurately Predicting Glutarylation Sites Using Sequential Bi-Peptide-Based Evolutionary Features

Abdollah Dehzangi, Swakkhar Shatabda, Md. Al Mehedi Hasan, 2020, Genes.

Ensemble of Neural Networks to Solve Class Imbalance Problem of Protein Secondary Structure Prediction

Abdollah Dehzangi, Maryam Alirezaee, Eghbal G. Mansoori, 2012 .

Introducing novel physicochemical based features to enhance protein fold prediction accuracy

Abdollah Dehzangi, B. G. Khosravi, Bahador Ganjeh Khosravi, 2010, 2010 International Conference On Computer Design and Applications.

Predicting protein-peptide binding sites with a Deep Convolutional Neural Network.

Abdollah Dehzangi, Mahmood A. Rashid, Tatsuhiko Tsunoda, 2020, Journal of theoretical biology.

Computational Prediction of Lysine Pupylation Sites in Prokaryotic Proteins Using Position Specific Scoring Matrix into Bigram for Feature Extraction

Abdollah Dehzangi, Daichi Shigemizu, Abel Avitesh Chandra, 2019, PRICAI.

C-iSUMO: A sumoylation site predictor that incorporates intrinsic characteristics of amino acid sequences

Yosvany López, Abdollah Dehzangi, Alok Sharma, 2020, Comput. Biol. Chem..

DeepAmp: A Convolutional Neural Network Based Tool for Predicting Protein AMPylation Sites From Binary Profile Representation

Sayed Mehedi Azim, Swakkhar Shatabda, A. Dehzangi, 2021 .

Using Random Forest for Protein Fold Prediction Problem: An Empirical Study

Abdollah Dehzangi, Somnuk Phon-Amnuaisuk, Omid Dehzangi, 2010, J. Inf. Sci. Eng..

The Application of Fusion of Heterogeneous Meta Classifiers to Enhance Protein Fold Prediction Accuracy

Abdollah Dehzangi, Sasan Karamizadeh, Roozbeh Hojabri Foladizadeh, 2011, ACIIDS.