By Dr Hamid Alinejad-Rokny

Book Chapters

Shabani N; Beheshti A; Farhood H; Bower M; Garrett M; Rokny HA, 2022, 'iCreate: Mining Creative Thinking Patterns from Contextualized Educational Data', in Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium, Springer International Publishing, pp. 352 - 356, http://dx.doi.org/10.1007/978-3-031-11647-6_68

Wang S; Beheshti A; Wang Y; Lu J; Sheng QZ; Elbourn S; Alinejad-Rokny H; Galanis E, 2021, 'Assessment2Vec: Learning Distributed Representations of Assessments to Reduce Marking Workload', in Artificial Intelligence in Education, pp. 384 - 389, http://dx.doi.org/10.1007/978-3-030-78270-2_68

Journal articles

Zahedi R; Ghamsari R; Argha A; Macphillamy C; Beheshti A; Alizadehsani R; Lovell NH; Lotfollahi M; Alinejad-Rokny H, 2024, 'Deep learning in spatially resolved transcriptfomics: A comprehensive technical view', Briefings in Bioinformatics, 25, http://dx.doi.org/10.1093/bib/bbae082

Jafari M; Sadeghi D; Shoeibi A; Alinejad-Rokny H; Beheshti A; García DL; Chen Z; Acharya UR; Gorriz JM, 2024, 'Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023', Applied Intelligence, 54, pp. 35 - 79, http://dx.doi.org/10.1007/s10489-023-05155-6

Islam S; Mugdha SBS; Dipta SR; Arafat ME; Shatabda S; Alinejad-Rokny H; Dehzangi I, 2024, 'MethEvo: an accurate evolutionary information-based methylation site predictor', Neural Computing and Applications, 36, pp. 201 - 212, http://dx.doi.org/10.1007/s00521-022-07738-9

Wang F; Alinejad-Rokny H; Lin J; Gao T; Chen X; Zheng Z; Meng L; Li X; Wong KC, 2023, 'A Lightweight Framework For Chromatin Loop Detection at the Single-Cell Level', Advanced Science, 10, http://dx.doi.org/10.1002/advs.202303502

Subramanian S; Thoms JAI; Huang Y; Cornejo-Páramo P; Koch FC; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll PS; Chacon-Fajardo D; Beck D; Curtis DJ; Yehson K; Antonenas V; O'Brien T; Trickett A; Powell JA; Lewis ID; Pitson SM; Gandhi MK; Lane SW; Vafaee F; Wong ES; Göttgens B; Alinejad-Rokny H; Wong JWH; Pimanda JE, 2023, 'Genome-wide transcription factor–binding maps reveal cell-specific changes in the regulatory architecture of human HSPCs', Blood, 142, pp. 1448 - 1462, http://dx.doi.org/10.1182/blood.2023021120

Shamsi A; Asgharnezhad H; Bouchani Z; Jahanian K; Saberi M; Wang X; Razzak I; Alizadehsani R; Mohammadi A; Alinejad-Rokny H, 2023, 'A novel uncertainty-aware deep learning technique with an application on skin cancer diagnosis', Neural Computing and Applications, 35, pp. 22179 - 22188, http://dx.doi.org/10.1007/s00521-023-08930-1

Parhami P; Fateh M; Rezvani M; Alinejad-Rokny H, 2023, 'A comparison of deep neural network models for cluster cancer patients through somatic point mutations', Journal of Ambient Intelligence and Humanized Computing, 14, pp. 10883 - 10898, http://dx.doi.org/10.1007/s12652-022-04351-5

Rahaie Z; Rabiee HR; Alinejad-Rokny H, 2023, 'DeepGenePrior: A deep learning model for prioritizing genes affected by copy number variants', PLoS Computational Biology, 19, http://dx.doi.org/10.1371/journal.pcbi.1011249

Ghamsari R; Rosenbluh J; Menon AV; Lovell NH; Alinejad-Rokny H, 2023, 'Technological Convergence: Highlighting the Power of CRISPR Single-Cell Perturbation Toolkit for Functional Interrogation of Enhancers', Cancers, 15, http://dx.doi.org/10.3390/cancers15143566

Jafari M; Shoeibi A; Khodatars M; Ghassemi N; Moridian P; Alizadehsani R; Khosravi A; Ling SH; Delfan N; Zhang YD; Wang SH; Gorriz JM; Alinejad-Rokny H; Acharya UR, 2023, 'Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review', Computers in Biology and Medicine, 160, http://dx.doi.org/10.1016/j.compbiomed.2023.106998

Khozeimeh F; Alizadehsani R; Shirani M; Tartibi M; Shoeibi A; Alinejad-Rokny H; Harlapur C; Sultanzadeh SJ; Khosravi A; Nahavandi S; Tan RS; Acharya UR, 2023, 'ALEC: Active learning with ensemble of classifiers for clinical diagnosis of coronary artery disease', Computers in Biology and Medicine, 158, http://dx.doi.org/10.1016/j.compbiomed.2023.106841

Shoeibi A; Khodatars M; Jafari M; Ghassemi N; Moridian P; Alizadehsani R; Ling SH; Khosravi A; Alinejad-Rokny H; Lam HK; Fuller-Tyszkiewicz M; Acharya UR; Anderson D; Zhang Y; Gorriz JM, 2023, 'Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review', Information Fusion, 93, pp. 85 - 117, http://dx.doi.org/10.1016/j.inffus.2022.12.010

Shabani N; Beheshti A; Farhood H; Bower M; Garrett M; Alinejad-Rokny H, 2023, 'A Rule-Based Approach for Mining Creative Thinking Patterns from Big Educational Data', AppliedMath, 3, pp. 243 - 267, http://dx.doi.org/10.3390/appliedmath3010014

Wang S; Beheshti A; Wang Y; Lu J; Sheng QZ; Elbourn S; Alinejad-Rokny H, 2023, 'Learning Distributed Representations and Deep Embedded Clustering of Texts', Algorithms, 16, http://dx.doi.org/10.3390/a16030158

Labani M; Beheshti A; Argha A; Alinejad-Rokny H, 2023, 'A Comprehensive Investigation of Genomic Variants in Prostate Cancer Reveals 30 Putative Regulatory Variants', International Journal of Molecular Sciences, 24, http://dx.doi.org/10.3390/ijms24032472

Alizadehsani R; Roshanzamir M; Izadi NH; Gravina R; Kabir HMD; Nahavandi D; Alinejad-Rokny H; Khosravi A; Acharya UR; Nahavandi S; Fortino G, 2023, 'Swarm Intelligence in Internet of Medical Things: A Review', Sensors, 23, http://dx.doi.org/10.3390/s23031466

Azim SM; Sabab NHN; Noshadi I; Alinejad-Rokny H; Sharma A; Shatabda S; Dehzangi I, 2023, 'Accurately predicting anticancer peptide using an ensemble of heterogeneously trained classifiers', Informatics in Medicine Unlocked, 42, http://dx.doi.org/10.1016/j.imu.2023.101348

Hong L; Modirrousta MH; Hossein Nasirpour M; Mirshekari Chargari M; Mohammadi F; Moravvej SV; Rezvanishad L; Rezvanishad M; Bakhshayeshi I; Alizadehsani R; Razzak I; Alinejad-Rokny H; Nahavandi S, 2023, 'GAN-LSTM-3D: An efficient method for lung tumour 3D reconstruction enhanced by attention-based LSTM', CAAI Transactions on Intelligence Technology, http://dx.doi.org/10.1049/cit2.12223

Hansun S; Argha A; Alinejad-Rokny H; Liaw ST; Celler BG; Marks GB, 2023, 'Revisiting Transfer Learning Method for Tuberculosis Diagnosis', Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, http://dx.doi.org/10.1109/EMBC40787.2023.10340441

Grapotte M; Saraswat M; Bessière C; Menichelli C; Ramilowski JA; Severin J; Hayashizaki Y; Itoh M; Tagami M; Murata M; Kojima-Ishiyama M; Noma S; Noguchi S; Kasukawa T; Hasegawa A; Suzuki H; Nishiyori-Sueki H; Frith MC; Abugessaisa I; Aitken S; Aken BL; Alam I; Alam T; Alasiri R; Alhendi AMN; Alinejad-Rokny H; Alvarez MJ; Andersson R; Arakawa T; Araki M; Arbel T; Archer J; Archibald AL; Arner E; Arner P; Asai K; Ashoor H; Astrom G; Babina M; Baillie JK; Bajic VB; Bajpai A; Baker S; Baldarelli RM; Balic A; Bansal M; Batagov AO; Batzoglou S; Beckhouse AG; Beltrami AP; Beltrami CA; Bertin N; Bhattacharya S; Bickel PJ; Blake JA; Blanchette M; Bodega B; Bonetti A; Bono H; Bornholdt J; Bttcher M; Bougouffa S; Boyd M; Breda J; Brombacher F; Brown JB; Bult CJ; Burroughs AM; Burt DW; Busch A; Caglio G; Califano A; Cameron CJ; Cannistraci CV; Carbone A; Carlisle AJ; Carninci P; Carter KW; Cesselli D; Chang JC; Chen JC; Chen Y; Chierici M; Christodoulou J; Ciani Y; Clark EL; Coskun M; Dalby M; Dalla E; Daub CO; Davis CA; de Hoon MJL; de Rie D; Denisenko E; Deplancke B; Detmar M; Deviatiiarov R; Di Bernardo D; Diehl AD; Dieterich LC, 2022, 'Author Correction: Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network (Nature Communications, (2021), 12, 1, (3297), 10.1038/s41467-021-23143-7)', Nature Communications, 13, http://dx.doi.org/10.1038/s41467-022-28758-y

Debnath T; Reza MM; Rahman A; Beheshti A; Band SS; Alinejad-Rokny H, 2022, 'Four-layer ConvNet to facial emotion recognition with minimal epochs and the significance of data diversity', Scientific Reports, 12, http://dx.doi.org/10.1038/s41598-022-11173-0

Dashti H; Dehzangi I; Bayati M; Breen J; Beheshti A; Lovell N; Rabiee HR; Alinejad-Rokny H, 2022, 'Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer', BMC Bioinformatics, 23, http://dx.doi.org/10.1186/s12859-022-04652-8

Ghareyazi A; Kazemi A; Hamidieh K; Dashti H; Tahaei MS; Rabiee HR; Alinejad-Rokny H; Dehzangi I, 2022, 'Pan-cancer integrative analysis of whole-genome De novo somatic point mutations reveals 17 cancer types', BMC Bioinformatics, 23, http://dx.doi.org/10.1186/s12859-022-04840-6

Rezaie N; Bayati M; Hamidi M; Tahaei MS; Khorasani S; Lovell NH; Breen J; Rabiee HR; Alinejad-Rokny H, 2022, 'Somatic point mutations are enriched in non-coding RNAs with possible regulatory function in breast cancer', Communications Biology, 5, http://dx.doi.org/10.1038/s42003-022-03528-0

Afrasiabi A; Alinejad-Rokny H; Khosh A; Rahnama M; Lovell N; Xu Z; Ebrahimi D, 2022, 'The low abundance of CpG in the SARS-CoV-2 genome is not an evolutionarily signature of ZAP', Scientific Reports, 12, pp. 2420, http://dx.doi.org/10.1038/s41598-022-06046-5

Subramanian S; Thoms JA; Huang Y; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll PS; Fajardo DC; Beck D; Curtis DJ; Yehson K; Antonenas V; O' Brien T; Trickett A; Powell J; Pitson SM; Gandhi MK; Cornejo P; Wong E; Lane SW; Gottgens B; Rokny HA; Wong JWH; Pimanda JE, 2022, 'Comparative Analysis of Genome-Scale Gene Regulatory Networks in Human Hematopoietic Stem and Myeloid Progenitor Fractions', BLOOD, 140, pp. 2846 - 2848, http://dx.doi.org/10.1182/blood-2022-165620

Truong P; Shen S; Joshi S; Afrasiabi A; Zhong L; Raftery MJ; Larsson J; Lock RB; Walkley CR; Rokny HA; Thoms JAI; Jolly CJ; Pimanda JE, 2022, 'Genome-Wide CRISPR-Cas9 Screening Identifies a Synergy between Hypomethylating Agents and Sumoylation Blockade in Myelodysplastic Syndromes and Acute Myeloid Leukemia', BLOOD, 140, http://dx.doi.org/10.1182/blood-2022-165713

Labani M; Beheshti A; Lovell NH; Alinejad-Rokny H; Afrasiabi A, 2022, 'KARAJ: An Efficient Adaptive Multi-Processor Tool to Streamline Genomic and Transcriptomic Sequence Data Acquisition', International Journal of Molecular Sciences, 23, http://dx.doi.org/10.3390/ijms232214418

MacPhillamy C; Alinejad-Rokny H; Pitchford WS; Low WY, 2022, 'Cross-species enhancer prediction using machine learning', Genomics, 114, http://dx.doi.org/10.1016/j.ygeno.2022.110454

Saberi-Movahed F; Mohammadifard M; Mehrpooya A; Rezaei-Ravari M; Berahmand K; Rostami M; Karami S; Najafzadeh M; Hajinezhad D; Jamshidi M; Abedi F; Mohammadifard M; Farbod E; Safavi F; Dorvash M; Mottaghi-Dastjerdi N; Vahedi S; Eftekhari M; Saberi-Movahed F; Alinejad-Rokny H; Band SS; Tavassoly I, 2022, 'Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods', Computers in Biology and Medicine, 146, http://dx.doi.org/10.1016/j.compbiomed.2022.105426

Band SS; Ardabili S; Yarahmadi A; Pahlevanzadeh B; Kiani AK; Beheshti A; Alinejad-Rokny H; Dehzangi I; Chang A; Mosavi A; Moslehpour M, 2022, 'A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis', Frontiers in Public Health, 10, http://dx.doi.org/10.3389/fpubh.2022.869238

Alinejad-Rokny H; Modegh RG; Rabiee HR; Sarbandi ER; Rezaie N; Tam KT; Forrest ARR, 2022, 'MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments', PLoS Computational Biology, 18, http://dx.doi.org/10.1371/journal.pcbi.1010241

Sharifonnasabi F; Jhanjhi NZ; John J; Obeidy P; Band SS; Alinejad-Rokny H; Baz M, 2022, 'Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography', Frontiers in Public Health, 10, http://dx.doi.org/10.3389/fpubh.2022.879418

Afrasiabi A; Keane JT; Ong LTC; Alinejad-Rokny H; Fewings NL; Booth DR; Parnell GP; Swaminathan S, 2022, 'Genetic and transcriptomic analyses support a switch to lytic phase in Epstein Barr virus infection as an important driver in developing Systemic Lupus Erythematosus', Journal of Autoimmunity, 127, http://dx.doi.org/10.1016/j.jaut.2021.102781

Razzak I; Naz S; Alinejad-Rokny H; Nguyen TN; Khalifa F, 2022, 'A Cascaded Mutliresolution Ensemble Deep Learning Framework for Large Scale Alzheimer's Disease Detection using Brain MRIs', IEEE/ACM Transactions on Computational Biology and Bioinformatics, http://dx.doi.org/10.1109/TCBB.2022.3219032

Argha A; Celler BG; Alinejad-Rokny H; Lovell NH, 2022, 'Blood Pressure Estimation From Korotkoff Sound Signals Using an End-to-End Deep-Learning-Based Algorithm', IEEE Transactions on Instrumentation and Measurement, 71, http://dx.doi.org/10.1109/TIM.2022.3217865

Sharifrazi D; Alizadehsani R; Joloudari JH; Band SS; Hussain S; Sani ZA; Hasanzadeh F; Shoeibi A; Dehzangi A; Sookhak M; Alinejad-Rokny H, 2022, 'CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering', Mathematical Biosciences and Engineering, 19, pp. 2381 - 2402, http://dx.doi.org/10.3934/MBE.2022110

Labani M; Afrasiabi A; Beheshti A; Lovell NH; Alinejad-Rokny H, 2022, 'PeakCNV: A multi-feature ranking algorithm-based tool for genome-wide copy number variation-association study', Computational and Structural Biotechnology Journal, 20, pp. 4975 - 4983, http://dx.doi.org/10.1016/j.csbj.2022.09.001

Grapotte M; Saraswat M; Bessière C; Menichelli C; Ramilowski JA; Severin J; Hayashizaki Y; Itoh M; Tagami M; Murata M; Kojima-Ishiyama M; Noma S; Noguchi S; Kasukawa T; Hasegawa A; Suzuki H; Nishiyori-Sueki H; Frith MC; Abugessaisa I; Aitken S; Aken BL; Alam I; Alam T; Alasiri R; Alhendi AMN; Alinejad-Rokny H; Alvarez MJ; Andersson R; Arakawa T; Araki M; Arbel T; Archer J; Archibald AL; Arner E; Arner P; Asai K; Ashoor H; Astrom G; Babina M; Baillie JK; Bajic VB; Bajpai A; Baker S; Baldarelli RM; Balic A; Bansal M; Batagov AO; Batzoglou S; Beckhouse AG; Beltrami AP; Beltrami CA; Bertin N; Bhattacharya S; Bickel PJ; Blake JA; Blanchette M; Bodega B; Bonetti A; Bono H; Bornholdt J; Bttcher M; Bougouffa S; Boyd M; Breda J; Brombacher F; Brown JB; Bult CJ; Burroughs AM; Burt DW; Busch A; Caglio G; Califano A; Cameron CJ; Cannistraci CV; Carbone A; Carlisle AJ; Carninci P; Carter KW; Cesselli D; Chang JC; Chen JC; Chen Y; Chierici M; Christodoulou J; Ciani Y; Clark EL; Coskun M; Dalby M; Dalla E; Daub CO; Davis CA; de Hoon MJL; de Rie D; Denisenko E; Deplancke B; Detmar M; Deviatiiarov R; Di Bernardo D; Diehl AD; Dieterich LC, 2021, 'Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network', Nature Communications, 12, http://dx.doi.org/10.1038/s41467-021-23143-7

MacPhillamy C; Pitchford WS; Alinejad-Rokny H; Low WY, 2021, 'Opportunity to improve livestock traits using 3D genomics', Animal Genetics, 52, pp. 785 - 798, http://dx.doi.org/10.1111/age.13135

Liu N; Low WY; Alinejad-Rokny H; Pederson S; Sadlon T; Barry S; Breen J, 2021, 'Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C', Epigenetics and Chromatin, 14, http://dx.doi.org/10.1186/s13072-021-00417-4

Pho KH; Akbarzadeh H; Parvin H; Nejatian S; Alinejad-Rokny H, 2021, 'A multi-level consensus function clustering ensemble', Soft Computing, 25, pp. 13147 - 13165, http://dx.doi.org/10.1007/s00500-021-06092-7

Walsh K; Gokool A; Alinejad-Rokny H; Voineagu I, 2021, 'NeuroCirc: an integrative resource of circular RNA expression in the human brain', Bioinformatics, 37, pp. 3664 - 3666, http://dx.doi.org/10.1093/bioinformatics/btab230

Ghareyazi A; Mohseni A; Dashti H; Beheshti A; Dehzangi A; Rabiee HR; Alinejad-Rokny H, 2021, 'Whole-genome analysis of de novo somatic point mutations reveals novel mutational biomarkers in pancreatic cancer', Cancers, 13, http://dx.doi.org/10.3390/cancers13174376

Afrasiabi A; Keane JT; Ik-Tsen Heng J; Palmer EE; Lovell NH; Alinejad-Rokny H, 2021, 'Quantitative neurogenetics: Applications in understanding disease', Biochemical Society Transactions, 49, pp. 1621 - 1631, http://dx.doi.org/10.1042/BST20200732

Rezaie N; Bayati M; Tahaei MS; Hamidi M; Khorasani S; Lovell NH; Breen J; Rabiee HR; Alinejad-Rokny H, 2021, 'Somatic point mutations are enriched in long non-coding RNAs with possible regulatory function in breast cancer', , http://dx.doi.org/10.1101/2021.07.19.453012

Shamshirband S; Fathi M; Dehzangi A; Chronopoulos AT; Alinejad-Rokny H, 2021, 'A review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues', Journal of Biomedical Informatics, 113, http://dx.doi.org/10.1016/j.jbi.2020.103627

Heidari R; Akbariqomi M; Asgari Y; Ebrahimi D; Alinejad-Rokny H, 2021, 'A systematic review of long non-coding RNAs with a potential role in breast cancer', Mutation Research - Reviews in Mutation Research, 787, http://dx.doi.org/10.1016/j.mrrev.2021.108375

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