Select Publications

Book Chapters

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 Lecture Notes in Computer Science, Springer International Publishing, pp. 384 - 389, http://dx.doi.org/10.1007/978-3-030-78270-2_68

Journal articles

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, vol. 12, http://dx.doi.org/10.1038/s41467-021-23143-7

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, vol. 14, http://dx.doi.org/10.1186/s13072-021-00417-4

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, vol. 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, vol. 49, pp. 1621 - 1631, http://dx.doi.org/10.1042/BST20200732

Voineagu I; Walsh K; Gokool A; Alinejad-Rokny H, 2021, 'NeuroCirc: An Integrative Resource of Circular RNA Expression In the Human Brain.', Bioinformatics, http://dx.doi.org/10.1093/bioinformatics/btab230

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

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, vol. 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, vol. 787, http://dx.doi.org/10.1016/j.mrrev.2021.108375

Mahmoudi MR; Akbarzadeh H; Parvin H; Nejatian S; Rezaie V; Alinejad-Rokny H, 2021, 'Consensus function based on cluster-wise two level clustering', Artificial Intelligence Review, vol. 54, pp. 639 - 665, http://dx.doi.org/10.1007/s10462-020-09862-1

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

Rajaei P; Jahanian KH; Beheshti A; Band SS; Dehzangi A; Alinejad-rokny H, 2021, 'VIRMOTIF: A user-friendly tool for viral sequence analysis', Genes, vol. 12, pp. 1 - 9, http://dx.doi.org/10.3390/genes12020186

Bayati M; Rabiee HR; Mehrbod M; Vafaee F; Ebrahimi D; Forrest ARR; Alinejad-Rokny H, 2020, 'CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes', Scientific Reports, vol. 10, pp. 1286, http://dx.doi.org/10.1038/s41598-020-58107-2

Alinejad-Rokny H; Heng JIT; Forrest ARR, 2020, 'Brain-Enriched Coding and Long Non-coding RNA Genes Are Overrepresented in Recurrent Neurodevelopmental Disorder CNVs', Cell Reports, vol. 33, http://dx.doi.org/10.1016/j.celrep.2020.108307

Afrasiabi A; Alinejad-Rokny H; Lovell N; Xu Z; Ebrahimi D, 2020, 'Insight into the origin of 5’UTR and source of CpG reduction in SARS-CoV-2 genome', , http://dx.doi.org/10.1101/2020.10.23.351353

Niu H; Xu W; Akbarzadeh H; Parvin H; Beheshti A; Alinejad-Rokny H, 2020, 'Deep feature learnt by conventional deep neural network', Computers and Electrical Engineering, vol. 84, http://dx.doi.org/10.1016/j.compeleceng.2020.106656

Bahrani P; Minaei-Bidgoli B; Parvin H; Mirzarezaee M; Keshavarz A; Alinejad-Rokny H, 2020, 'User and item profile expansion for dealing with cold start problem', Journal of Intelligent & Fuzzy Systems, vol. 38, pp. 4471 - 4483, http://dx.doi.org/10.3233/jifs-191225

Khakmardan S; Rezvani M; Pouyan AA; Fateh M; Alinejad-Rokny H, 2020, 'MHiC, an integrated user-friendly tool for the identification and visualization of significant interactions in Hi-C data', BMC Genomics, vol. 21, http://dx.doi.org/10.1186/s12864-020-6636-7

Niu H; Khozouie N; Parvin H; Alinejad-Rokny H; Beheshti A; Mahmoudi MR, 2020, 'An ensemble of locally reliable cluster solutions', Applied Sciences (Switzerland), vol. 10, pp. 1891 - 1891, http://dx.doi.org/10.3390/app10051891

Hosseinpoor M; Parvin H; Nejatian S; Rezaie V; Bagherifard K; Dehzangi A; Beheshti A; Alinejad-Rokny H, 2020, 'Proposing a novel community detection approach to identify co-interacting genomic regions', Mathematical Biosciences and Engineering, vol. 17, pp. 2193 - 2217, http://dx.doi.org/10.3934/mbe.2020117

Masoudiasl I; Vahdat S; Hessam S; Shamshirband S; Alinejad-Rokny H, 2019, 'Proposing an Integrated Method based on Fuzzy Tuning and ICA Techniques to Identify the Most Influencing Features in Breast Cancer', Iranian Red Crescent Medical Journal, vol. 21, http://dx.doi.org/10.5812/ircmj.92077

Woodward KJ; Stampalia J; Vanyai H; Rijhumal H; Potts K; Taylor F; Peverall J; Grumball T; Sivamoorthy S; Alinejad-Rokny H; Wray J; Whitehouse A; Nagarajan L; Scurlock J; Afchani S; Edwards M; Murch A; Beilby J; Baynam G; Kiraly-Borri C; McKenzie F; Heng JIT, 2019, 'Atypical nested 22q11.2 duplications between LCR22B and LCR22D are associated with neurodevelopmental phenotypes including autism spectrum disorder with incomplete penetrance', Molecular Genetics and Genomic Medicine, vol. 7, http://dx.doi.org/10.1002/mgg3.507

Vafaee F; Diakos C; Kirschner M; Reid G; Michael M; Horvath LISA; Alinejad-Rokny H; Cheng ZJ; Kuncic Z; Clarke S, 2018, 'A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis', npj Systems Biology and Applications, vol. 4, pp. 20 - 20, http://dx.doi.org/10.1038/s41540-018-0056-1

Vafaee F; Dashti H; Alinejad-Rokny H, 2018, 'Transcriptomic Data Normalization', Encyclopedia of Bioinformatics and Computational Biology, Elsevier, http://dx.doi.org/10.1016/B978-0-12-809633-8.20209-4

Kalantari A; Kamsin A; Shamshirband S; Gani A; Alinejad-Rokny H; Chronopoulos AT, 2018, 'Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions', Neurocomputing, vol. 276, pp. 2 - 22, http://dx.doi.org/10.1016/j.neucom.2017.01.126

Alinejad-Rokny H; Sadroddiny E; Scaria V, 2018, 'Machine learning and data mining techniques for medical complex data analysis', Neurocomputing, vol. 276, pp. 1, http://dx.doi.org/10.1016/j.neucom.2017.09.027

Poulton C; Baynam G; Yates C; Alinejad-Rokny H; Williams S; Wright H; Woodward KJ; Sivamoorthy S; Peverall J; Shipman P; Ravine D; Beilby J; Heng JIT, 2018, 'A review of structural brain abnormalities in Pallister-Killian syndrome', Molecular Genetics and Genomic Medicine, vol. 6, pp. 92 - 98, http://dx.doi.org/10.1002/mgg3.351

Baghernia A; Pavin H; Mirnabibaboli M; Alinejad-Rokny H, 2017, 'Clustering High-Dimensional Data Stream: A Survey on Subspace Clustering, Projected Clustering on Bioinformatics Applications (Advanced Science, Engineering and Medicine, Vol. 8(9), pp. 749–757 (2016))', Advanced Science, Engineering and Medicine, vol. 9, pp. 617 - 617, http://dx.doi.org/10.1166/asem.2017.2063

Alinejad-Rokny H; Parvin H; Ahangarikiasari H, 2017, 'Pattern Mining and Identifying Co-Expressed Genes from RNA-Seq Dataset Using a New Swarm Intelligence-Based Clustering (Advanced Science, Engineering and Medicine, Vol. 9(1), pp. 36–45 (2017))', Advanced Science, Engineering and Medicine, vol. 9, pp. 618 - 618, http://dx.doi.org/10.1166/asem.2017.2064

Alinejad-Rokny H, 2017, 'A Method to Avoid Gapped Sequential Patterns in Biological Sequences: Case Study: HIV and Cancer Sequences', Journal of Neuroscience and Neuroengineering, vol. 4, pp. 49 - 53, http://dx.doi.org/10.1166/jnsne.2017.1114

Alinejad-Rokny H; Parvin H; Ahangarikiasari H, 2017, 'Pattern Mining and Identifying Co-Expressed Genes from RNA-Seq Dataset Using a New Swarm Intelligence-Based Clustering', Advanced Science, Engineering and Medicine, vol. 9, pp. 36 - 45, http://dx.doi.org/10.1166/asem.2017.1959

Alinejad-Rokny H; Anwar F; Waters SA; Davenport MP; Ebrahimi D, 2016, 'Source of CpG depletion in the HIV-1 genome', Molecular Biology and Evolution, vol. 33, pp. 3205 - 3212, http://dx.doi.org/10.1093/molbev/msw205

Alinejad-Rokny H; Masoud M, 2016, 'A method for hypermutated viral sequences detection in fastq and bam format files', Journal of Medical Imaging and Health Informatics, vol. 6, pp. 1202 - 1208, http://dx.doi.org/10.1166/jmihi.2016.1977

Baghernia A; Pavin H; Mirnabibaboli M; Alinejad-Rokny H, 2016, 'Clustering High-Dimensional Data Stream: A Survey on Subspace Clustering, Projected Clustering on Bioinformatics Applications', Advanced Science, Engineering and Medicine, vol. 8, pp. 749 - 757, http://dx.doi.org/10.1166/asem.2016.1915

Lloyd SB; Lichtfuss M; Amarasena TH; Alcantara S; De Rose R; Tachedjian G; Alinejad-Rokny H; Venturi V; Davenport MP; Winnall WR; Kent SJ, 2016, 'High fidelity simian immunodeficiency virus reverse transcriptase mutants have impaired replication in vitro and in vivo', Virology, vol. 492, pp. 1 - 10, http://dx.doi.org/10.1016/j.virol.2016.02.008

Alinejad-Rokny H, 2016, 'Proposing on optimized homolographic motif mining strategy based on parallel computing for complex biological networks', Journal of Medical Imaging and Health Informatics, vol. 6, pp. 416 - 424, http://dx.doi.org/10.1166/jmihi.2016.1707

Alinejad-Rokny H; Ebrahimi D, 2015, 'A method to avoid errors associated with the analysis of hypermutated viral sequences by alignment-based methods', Journal of Biomedical Informatics, vol. 58, pp. 220 - 225, http://dx.doi.org/10.1016/j.jbi.2015.10.008

Martyushev AP; Petravic J; Grimm AJ; Alinejad-Rokny H; Gooneratne SL; Reece JC; Cromer D; Kent SJ; Davenport MP, 2015, 'Epitope-specific CD8+ T cell kinetics rather than viral variability determine the timing of immune escape in simian immunodeficiency virus infection', Journal of Immunology, vol. 194, pp. 4112 - 4121, http://dx.doi.org/10.4049/jimmunol.1400793

Parvin H; Mirnabibaboli M; Alinejad-Rokny H, 2015, 'Proposing a classifier ensemble framework based on classifier selection and decision tree', Engineering Applications of Artificial Intelligence, vol. 37, pp. 34 - 42, http://dx.doi.org/10.1016/j.engappai.2014.08.005

Ahmadinia M; Alinejad-Rokny H; Ahangarikiasari H, 2014, 'Data Aggregation in Wireless Sensor Networks Based on Environmental Similarity: A Learning Automata Approach', Journal of Networks, vol. 9, http://dx.doi.org/10.4304/jnw.9.10.2567-2573

Jamnejad MI; Parvin H; Alinejad-Rokny H; Heidarzadegan A, 2014, 'Proposing a New Method Based on Linear Discriminant Analysis to Build a Robust Classifier', Journal of Bioinformatics and Intelligent Control, vol. 3, pp. 186 - 193, http://dx.doi.org/10.1166/jbic.2014.1086

Jamnejad I; Heidarzadegan A; Parvin H; Alinejad-Rokny H, 2014, 'Localizing program bugs based on program invariant', International Journal of Computing and Digital Systems, vol. 3, pp. 141 - 150, http://dx.doi.org/10.12785/IJCDS/030208

Mokhtari SM; Alinejad-Rokny H; Jalalifar H, 2014, 'Selection of the best well control system by using fuzzy multiple-attribute decision-making methods', Journal of Applied Statistics, vol. 41, pp. 1105 - 1121, http://dx.doi.org/10.1080/02664763.2013.862218

Ebrahimi D; Alinejad-Rokny H; Davenport MP, 2014, 'Insights into the motif preference of APOBEC3 enzymes', PLoS ONE, vol. 9, http://dx.doi.org/10.1371/journal.pone.0087679

Minaei-Bidgoli B; Parvin H; Alinejad-Rokny H; Alizadeh H; Punch WF, 2014, 'Effects of resampling method and adaptation on clustering ensemble efficacy', Artificial Intelligence Review, vol. 41, pp. 27 - 48, http://dx.doi.org/10.1007/s10462-011-9295-x

Gooneratne SL; Alinejad-Rokny H; Ebrahimi D; Bohn PS; Wiseman RW; O'Connor DH; Davenport MP; Kent SJ, 2014, 'Linking pig-tailed macaque major histocompatibility complex class I haplotypes and cytotoxic T lymphocyte escape mutations in simian immunodeficiency virus infection', Journal of Virology, vol. 88, pp. 14310 - 14325, http://dx.doi.org/10.1128/JVI.02428-14

Alinejad-Rokny H; Pourshaban H; Orimi AG; Baboli MM, 2014, 'Network motifs detection strategies and using for bioinformatic networks', Journal of Bionanoscience, vol. 8, pp. 353 - 359, http://dx.doi.org/10.1166/jbns.2014.1245

Parvin H; Minaei-Bidgoli B; Alinejad-Rokny H, 2013, 'A new imbalanced learning and dictions tree method for breast cancer diagnosis', Journal of Bionanoscience, vol. 7, pp. 673 - 678, http://dx.doi.org/10.1166/jbns.2013.1162

Javanmard R; JeddiSaravi K; Alinejad-Rokny H, 2013, 'Proposed a new method for rules extraction using artificial neural network and artificial immune system in cancer diagnosis', Journal of Bionanoscience, vol. 7, pp. 665 - 672, http://dx.doi.org/10.1166/jbns.2013.1160

Ahmadinia M; Meybodi M; Esnaashari M; Alinejad-Rokny H, 2013, 'Energy-efficient and multi-stage clustering algorithm in wireless sensor networks using cellular learning automata', IETE Journal of Research, vol. 59, pp. 774 - 782, http://dx.doi.org/10.4103/0377-2063.126958


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