Abdollah 'Iman' Dehzangi

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Alok SharmaSenior Scientist at RIKEN; University of the South Pacific; Griffith UniversityDirección de correo verificada de griffith.edu.au
Kuldip PaliwalProfessor (Chair, Communication and Information Engineering), Griffith University, BrisbaneDirección de correo verificada de griffith.edu.au
James LyonsUnaffiliatedDirección de correo verificada de griffithuni.edu.au
Abdul SattarProfessor of Computer Science, Griffith UniversityDirección de correo verificada de griffith.edu.au
Rhys HeffernanGriffith UniversityDirección de correo verificada de griffith.edu.au
Tatsuhiko TsunodaProfessor, The University of TokyoDirección de correo verificada de bs.s.u-tokyo.ac.jp
Yaoqi ZhouProfessor, Institute for Glycomics and School of Information and Communication Technology, GriffithDirección de correo verificada de griffith.edu.au
Yuedong YangSchool of Data and Computer Science, Sun Yat-sen UniversityDirección de correo verificada de mail.sysu.edu.cn
Gazelle TaherzadehUniversity of MarylandDirección de correo verificada de griffithuni.edu.au
Somnuk Phon-AmnuaisukUniversiti Teknologi BruneiDirección de correo verificada de utb.edu.bn
Yosvany López, Ph.D.GENEWIZDirección de correo verificada de brooks.com
Harsh SainiUniversity of the South PacificDirección de correo verificada de usp.ac.fj
Seiya ImotoProfessor of Institute of Medical Science, University of TokyoDirección de correo verificada de ims.u-tokyo.ac.jp
Dewan Md. FaridAssociate Professor, Dept. of Computer Science & Engineering, United International UniversityDirección de correo verificada de cse.uiu.ac.bd
Farshid RayhanComputer Science, The University of ManchesterDirección de correo verificada de manchester.ac.uk
Mahmood A. RashidVictoria University Melbourne, AustraliaDirección de correo verificada de vu.edu.au
Sasan KaramizadehResearcher at The ICT Research InstituteDirección de correo verificada de itrc.ac.ir
Zaynab MousavianUniversity of TehranDirección de correo verificada de ut.ac.ir
Sohrab SohrabiSPL LABDirección de correo verificada de griffithuni.edu.au
Mahmoud ManafiDr of Business Administration and PhD Candidate of MathematicsDirección de correo verificada de fc.up.pt

Abdollah 'Iman' Dehzangi

Assistant Professor at the Department of Computer Science, Rutgers University

Dirección de correo verificada de rutgers.edu

Computational Biology Bioinformatics Pattern Recognition Machine learning Artificial Intelligence


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Improving prediction of secondary structure, local backbone angles and solvent accessible surface area of proteins by iterative deep learning R Heffernan, K Paliwal, J Lyons, A Dehzangi, A Sharma, J Wang, A Sattar, ... Scientific reports 5 (1), 1-11, 2015	281	2015
Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou׳ s general PseAAC A Dehzangi, R Heffernan, A Sharma, J Lyons, K Paliwal, A Sattar Journal of theoretical biology 364, 284-294, 2015	231	2015
A feature extraction technique using bi-gram probabilities of position specific scoring matrix for protein fold recognition A Sharma, J Lyons, A Dehzangi, KK Paliwal Journal of theoretical biology 320, 41-46, 2013	141	2013
Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto‐encoder deep neural network J Lyons, A Dehzangi, R Heffernan, A Sharma, K Paliwal, A Sattar, Y Zhou, ... Journal of computational chemistry 35 (28), 2040-2046, 2014	125	2014
Spider2: A package to predict secondary structure, accessible surface area, and main-chain torsional angles by deep neural networks Y Yang, R Heffernan, K Paliwal, J Lyons, A Dehzangi, A Sharma, J Wang, ... Prediction of protein secondary structure, 55-63, 2017	110	2017
Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins R Heffernan, A Dehzangi, J Lyons, K Paliwal, A Sharma, J Wang, A Sattar, ... Bioinformatics 32 (6), 843-849, 2016	80	2016
Predict gram-positive and gram-negative subcellular localization via incorporating evolutionary information and physicochemical features into Chou's general PseAAC R Sharma, A Dehzangi, J Lyons, K Paliwal, T Tsunoda, A Sharma IEEE transactions on nanobioscience 14 (8), 915-926, 2015	78	2015
A tri-gram based feature extraction technique using linear probabilities of position specific scoring matrix for protein fold recognition KK Paliwal, A Sharma, J Lyons, A Dehzangi IEEE transactions on nanobioscience 13 (1), 44-50, 2014	69	2014
A combination of feature extraction methods with an ensemble of different classifiers for protein structural class prediction problem A Dehzangi, K Paliwal, A Sharma, O Dehzangi, A Sattar IEEE/ACM Transactions on Computational Biology and Bioinformatics 10 (3 …, 2013	59	2013
iDTI-ESBoost: identification of drug target interaction using evolutionary and structural features with boosting F Rayhan, S Ahmed, S Shatabda, DM Farid, Z Mousavian, A Dehzangi, ... Scientific reports 7 (1), 1-18, 2017	58	2017
Using random forest for protein fold prediction problem: an empirical study. A Dehzangi, S Phon-Amnuaisuk, O Dehzangi J. Inf. Sci. Eng. 26 (6), 1941-1956, 2010	57	2010
A strategy to select suitable physicochemical attributes of amino acids for protein fold recognition A Sharma, KK Paliwal, A Dehzangi, J Lyons, S Imoto, S Miyano BMC bioinformatics 14 (1), 1-11, 2013	51	2013
SucStruct: prediction of succinylated lysine residues by using structural properties of amino acids Y López, A Dehzangi, SP Lal, G Taherzadeh, J Michaelson, A Sattar, ... Analytical biochemistry 527, 24-32, 2017	46	2017
iDNAProt-ES: Identification of dna-binding proteins using evolutionary and structural features SY Chowdhury, S Shatabda, A Dehzangi Scientific reports 7 (1), 1-14, 2017	45	2017
A Segmentation-based Method to Extract Structural and Evolutionary Features for Protein Fold Recognition A Dehzangi, J Lyons, A Sharma, A Sattar IEEE/ACM Transactions on Computational Biology and Bioinformatics 11 (3 …, 2014	44	2014
Proposing a highly accurate protein structural class predictor using segmentation-based features A Dehzangi, K Paliwal, J Lyons, A Sharma, A Sattar BMC genomics 15 (1), 1-13, 2014	43	2014
PSSM-Suc: Accurately predicting succinylation using position specific scoring matrix into bigram for feature extraction A Dehzangi, Y López, SP Lal, G Taherzadeh, J Michaelson, A Sattar, ... Journal of theoretical biology 425, 97-102, 2017	42	2017
Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction Y López, A Sharma, A Dehzangi, SP Lal, G Taherzadeh, A Sattar, ... BMC Genomics 19 (Suppl 1), 923, 2018	35	2018
Advancing the accuracy of protein fold recognition by utilizing profiles from hidden Markov models J Lyons, A Dehzangi, R Heffernan, Y Yang, Y Zhou, A Sharma, K Paliwal IEEE transactions on nanobioscience 14 (7), 761-772, 2015	33	2015
Protein fold recognition by alignment of amino acid residues using kernelized dynamic time warping J Lyons, N Biswas, A Sharma, A Dehzangi, KK Paliwal Journal of theoretical biology 354, 137-145, 2014	33	2014

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