*******About*******

An independent and collaborative academic researcher (with Doctor of Philosophy in Computer Science)  specialized in the Artificial Intelligence (Machine Learning) field with record of peer-reviewed publications, gaining experience over many years tackling real problems in various fields (primarily biology, social media, and others)

PhD Thesis: Development and evaluation of machine learning algorithms for biomedical applications


8 AI courses (Taken in-person during MS and PhD):

(NJIT, NYU, Stanford University): Artificial Intelligence; Foundations of Machine Learning; Machine Learning; ST: Machine Learning;  Pattern Recognition & Applications; Data Mining (Department of CS); Data Mining & Management in Bioinformatics; Data Mining (Department of Statistics).

*******News*******

Paper with MS Student, Mansour Almutaani, and Dr. Y-h. Taguchi has been published at Scientific Reports (Nature), 2024 (https://doi.org/10.1038/s41598-024-76498-4 Or here at https://rdcu.be/dY0e0 ). This work presents a computational framework to expand the model space and thereby identify a potentially better performing model than existing ones when tackling the COVID-19 classification task using X-ray and CT images. Reported results demonstrated the usefulness of the proposed framework in identifying a better performing DL models than existing ones including transformer-based models such as ViT, Swin, FasterViT, and SHViT.  
- Pleased to join the editorial board of BMC Artificial Intelligence (https://bmcartificialintel.biomedcentral.com/about/editorial-board).
-Paper with MS student Sarah Al Habib and Dr. Y-h. Taguchi has been published at Mathematics (MDPI) , 2024 (https://www.mdpi.com/2227-7390/12/10/1573). Congratulations Sarah. In this novel work, we employ deep transfer learning to tackle the COVID-19 classification task using transmission electron microscopy images pertaining to healthy and infected human alveolar type II cells with SARS-CoV-2. Experimental results demonstrate the high performance results of TFeDenseNet201, promoting to a successful AI application in respiratory diseases.
-Paper with Dr. Y-h. Taguchi has been published at Mathematics (MDPI), 2024 (https://www.mdpi.com/2227-7390/12/10/1536). In this paper, we present a computationally efficient (and superior) tool (https://aibio.shinyapps.io/maGENEgerZ/) to tackle the high dimensional issue and extract various biological knowledge pertaining to breast cancer drug response mechanism. According to extensive experiments, our tool outperforms from biological and classification perspectives several bioinformatics-based and deep learning-based tools such as limma, sam, DeepLIFT, and DeepSHAP, in addition to other tools.
- Paper with PhD Student, Sumaya Alghamdi, has been published at Scientific Reports (Nature), 2024 (https://doi.org/10.1038/s41598-024-54923-y Or here https://rdcu.be/dztqi). Congratulations Sumaya for the solid work pertaining to explaining and promoting what leads to the superiority of deep learning models under the transfer learning setting when tackling the target task of predicting T2D based on single-cell gene regulatory networks. This work sets the foundation for building efficient deep transfer leaning models.
-Paper entitled "GENEvaRX: A Novel AI-Driven Method and Web Tool Can Identify Critical Genes and Effective Drugs for Lichen Planus" has been accepted at Engineering Applications of Artificial Intelligence (https://authors.elsevier.com/a/1hMZ63OWJ94qgd). As lichen planus is a complex disease with no cure (up-to-date), we developed GENEvaRX (https://aibio.shinyapps.io/GENEvaRX/), AI-based web tool, to address the medical community needs via identifying therapeutic targets, drug targets, and drugs as well as important genes pertaining to lichen planus. Moreover, GENEvaRX pointed to B vitamins as a treatment coinciding with first medical attempt to successfully treat LP. These results show that our AI-based framework can assist doctors and identify effective treatments for patients, in addition to time and cost saving in the medical sector.
- Paper with MS Student, Hamed Alghamdi, has been published in Agriculture (MDPI) at (https://www.mdpi.com/2077-0472/13/5/1072). Congratulations Hamed!
- Work with MS Student, Wael Alhazmi, has been published in Diagnostics (MDPI) at (https://www.mdpi.com/2075-4418/13/10/1721). Congratulations Wael!
-Leading with Prof. Wei a Special Session, entitled "AI Techniques for Myriad Automation: Methodologies Meet Successful Real-Life Applications" at the 2023 International Conference on Cyber-physical Social Intelligence (https://agist.org/iccsi2023/files/Accepted_Special_Sessions/S23.pdf). Full Paper Submission Deadline: May 15, 2023
-Organizing committee member at the 2023 International Conference on Cyber-physical Social Intelligence(https://agist.org/iccsi2023/Organizing_committee.html), October 20-23, 2023, xi'an, China
-Leading with Prof. Wei a Special Issue "Bioinformatics and Cells" in Cells (IF: 6:6) (https://www.mdpi.com/journal/cells/special_issues/Computational_Cells)
-Invited to Join "Novel Methods and Applications of Executable Regulatory Network Models in Systems Research" as a guest editor at Frontiers in Systems Biology (https://www.frontiersin.org/research-topics/37097/novel-methods-and-applications-of-executable-regulatory-network-models-in-systems-research)
-Invited to join "Multiomic Characterization and Therapeutic Targets of Brain Metastases across Primary Cancer Types" as a a guest editor at Frontiers in Genetics - Cancer Genetics and Oncogenomics (https://www.frontiersin.org/research-topics/36683/multiomic-characterization-and-therapeutic-targets-of-brain-metastases-across-primary-cancer-types)
-Leading with Prof. Wei a Speacial Issue "Automation of Intellectual Tasks via Machine Learning for Data Science" in ICCSI 2022 (https://iccsi2022.agist.org/acceptedSS.html). Link to CFP: https://iccsi2022.agist.org/files/Accepted_Special_Sessions/SS09.pdf

Teaching:
CS661: Advanced Artificial Intelligence
CPCS433: Artificial Intelligence Topics

-As I have several projects that would lead to a Masters or PhD thesis as well as undergraduate projects, I am looking for graduate (and undergraduate) students interested to work on problems in biology and medicine using AI (e.g., machine learning or deep learning). Please email me if you are interested.

-Our study (led by Dr. Y-h. Taguchi) pertaining to Drug Discovery for COVID-19 was advertised by Scientia,
https://www.scientia.global/dr-y-h-taguchi-in-silico-drug-discovery-for-covid-19-using-an-unsupervised-feature-extraction-method/

-Recently published article entitled "Novel method for the prediction of drug-drug Interaction based on gene expression profiles" led by Dr. Y-h. Taguchi appearing at Pharma Focus Asia https://www.pharmafocusasia.com/articles/is-convex-dose-dependence-a-side-effect-that-multiple-drug-treatment-causes.  Also was a top story of March e-newsletter

-Works on COVID-19 (https://tagtag.github.io/COVID-19-en.html) led by Dr. Y-h. Taguchi were registered in "AI-enabled research activities for COVID-19" https://www.ai-japan.go.jp/en/COVID19 under the AI Japan R&D Network

-Leading with Dr. Y-h. Taguchi a Research Topic on "Machine Intelligence in Single-Cell Data Analysis: Advances and New Problems". https://www.frontiersin.org/research-topics/15609/machine-intelligence-in-single-cell-data-analysis-advances-and-new-problems


Journal Editorial Board:

- BMC Artificial Intelligence (https://bmcartificialintel.biomedcentral.com/about/editorial-board).
-Computers in Biology and Medicine (https://www.journals.elsevier.com/computers-in-biology-and-medicine/editorial-board). Impact Factor: 6.698 (2022)
-Sustainable Computing: Informatics and Systems (https://www.journals.elsevier.com/sustainable-computing-informatics-and-systems/editorial-board). Impact Factor: 4.923 (2022)
-BMC Medical Genomics (https://bmcmedgenomics.biomedcentral.com/about/editorial-board). Impact Factor: 3.063 (2022)
-PLOS ONE (Academic Editor) (https://journals.plos.org/plosone/). Impact Factor: 3.240 (2022)
-Informatics in Medicine Unlocked (https://www.journals.elsevier.com/informatics-in-medicine-unlocked/editorial-board/turki-turki-phd).
-Frontiers in Artificial Intelligence (Review Editor) (https://www.frontiersin.org/journals/artificial-intelligence#)
-Frontiers in Big Data (Review Editor) (https://www.frontiersin.org/journals/big-data)

Journal Reviewer:
-Nature Communications (Nature).
-PLOS Computational Biology.
-Briefings in Bioinformatics (Oxford).
-Bioinformatics (Oxford).
-Scientific Reports (Nature).
-Journal of Hazardous Materials (Elsevier).
-Information Sciences (Elsevier).
-IEEE Transactions on Neural Networks and Learning Systems.
-Applied Soft Computing (Elsevier).
-Computers in Biology and Medicine (Elsevier).
-IEEE Journal of Biomedical and Health Informatics
-PLOS ONE (PLOS).
-Computational and Structural Biotechnology Journal (Elsevier).
-Photonic Sensors (Springer)
-The Innovation: Cell Press
-Tumor Biology (SAGE).
-Journal of Bioinformatics and Computational Biology (Imperial College Press).
-Informatics in Medicine Unlocked (Elsevier).
-IEEE Access

Students:

Current
Fares Jammal (PhD, Computer Science)
Emad Kaen (PhD, Computer Science)
Sumaya Alghamdi (PhD, Computer Science)
Abdullah Alsaiari (MS, Computer Science)
Mohammed Alnaqash (MS, Computer Science)
Sarah Abdulrahman Al Habib‎ (MS, Computer Science)
Mansour Al Metani (MS, Computer Science)

Past
Hamed Alghamdi (MS, Computer Science), 2022-2023
Wael Humaidan M Alhazmi (MS, Computer Science), 2022-2023
Abdulaziz Alghamdi (BS, Computer Science), 2022
Abdulaziz Almutari (BS, Computer Science), 2022
Muhannad Binmahfouz (BS, Computer Science), 2022
Nasir ALDamadi (BS, Computer Science), 2022
Anmar Al-Sharif (MS, Computer Science), 2021-2022
Khalil Aljohani (MS, Computer Science), 2021-2022
Talal Al Qurashi (BS, Computer Science), 2021
Firas Mahmoud (BS, Computer Science, 2021
Younes Alturkey (BS, Computer Science), 2021
Mohammed Alshutiari (BS, Computer Science), 2021
Abdullah Albukhari (BS, Computer Science), 2021
Odai Al-Ghamdi, BS Computer Science, 2019
Emad Kaen, MS Computer Science, 2019, co-advised with Dr. Abdullah Algarni

Publications:

-Mansour Almutaani, Turki Turki, and Y-h. Taguchi, "Novel large empirical study of deep transfer learning for COVID-19 classification based on CT and X-ray images," Accepted at Scientific Reports (Nature), 2024
- Y-h. Taguchi and Turki Turki, "Novel AI-powered computational method using tensor decomposition can discover the common optimal bin sizes when integrating multiple Hi-C datasets," bioRxiv, 2024.
- Y-h. Taguchi and Turki Turki, "Novel artificial intelligence-based identification of drug-gene-disease interaction through using protein-protein interaction," bioRxiv, 2024.
-Turki Turki, Sarah Al Habib, and Y-h. Taguchi, "Novel Automatic Classification of Human Adult Lung Alveolar Type II Cells Infected with SARS-CoV-2 through the Deep Transfer Learning Approach," Mathematics (MDPI), 2024. IF: 2.4.
-Turki Turki and Y-h. Taguchi, "maGENEgerZ: An Efficient Artificial Intelligence-Based Framework Can Extract More Expressed Genes and Biological Insights Underlying Breast Cancer Drug Response Mechanism," Mathematics (MDPI), 2024. IF: 2.4.
- Sumaya Alghamdi and Turki Turki, "A novel interpretable deep transfer learning combining diverse learnable parameters for improved T2D prediction based on single-cell gene regulatory networks," Accepted at Scientific Reports (Nature), 2024. IF: 4.6.
 -Turki Turki,  Sanjiban Sekhar Roy, and Y-h. Taguchi,  "Optimized Tensor Decomposition and PCA Outperforming State-of-the-Art Methods When Analyzing Histone Modification ChIP-seq Profiles," Accepted at Algorithms (MDPI), 2023. IF: 2.3
 -Y-h. Taguchi and Turki Turki,  " Integrated analysis of gene expression and protein-protein interaction with tensor decomposition," Accepted at Mathematics (MDPI), 2023. IF: 2.4
-Y-h. Taguchi and Turki Turki, "TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extraction," Frontiers in Artificial Intelligence, 2023. IF: 4
-Turki Turki and Y-h. Taguchi, "GENEvaRX: A Novel AI-Driven Method and Web Tool Can Identify Critical Genes and Effective Drugs for Lichen Planus,"  Accepted at Engineering Applications of Artificial Intelligence (Elsevier), 2023. IF: 8.
-Hamed Alghamdi and Turki Turki, "PDD-Net: Plant Disease Diagnoses Using Multilevel and Multiscale Convolutional Neural Network Features," Agriculture (MDPI), 2023. IF: 3.408
-Wael Alhazmi and Turki Turki, "Applying Deep Transfer Learning to Assess the Impact of Imaging Modalities on Colon Cancer Detection," Diagnostics (MDPI), 2023. IF: 3.992
- Y-h. Taguchi and Turki Turki, "Tensor Decomposition Discriminates Tissues Using scATAC-seq," Accepted at BBA - General Subject (Elsevier) , 2023. IF: 4.117
-Y-h. Taguchi and Turki Turki, "Principal component analysis- and tensor decomposition-based unsupervised feature extraction to select more reasonable differentially methylated cytosines: Optimization of standard deviation versus state-of-the-art methods," Accepted at Genomics (Elsevier), 2023. IF: 4.31
-Turki Turki and Y-h. Taguchi, "A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells," Accepted at Gene (Elsevier), 2023. Acceptance Rate: 12%. IF: 3.913.
-Arif Ahmed Sk, Turki Turki, Tarun Kumar Ghosh, Subhankar Joardar, Subhabrata Barman, "Artificial Intelligence: First International Symposium, ISAI 2022, Haldia, India, February 17-22, 2022, Revised Selected Papers", Springer
-Y-h. Taguchi and Turki Turki, "A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching," accepted at Scientific Reports (Nature), 2022, IF: 4.996
-Y-h. Taguchi and Turki Turki, "Adapted Tensor decomposition and PCA based unsupervised feature extraction select more biologically reasonable differentially expressed genes than conventional methods," accepted at Scientific Reports (Nature), 2022, IF: 4.996.
-Y-h. Taguchi and Turki Turki, "Projection in genomic analysis: A theoretical basis to rationalize tensor decomposition and principal component analysis as feature selection tools," PLOS ONE, 2022, IF: 3.752.
-Turki Turki and SANJIBAN SEKHAR ROY, "Novel hate speech detection using word cloud visualization and ensemble learning coupled with count vectorizer, " Accepted at Applied Sciences (MDPI), 2022. IF: 2.679
-Khalil Aljohani and Turki Turki, "AUTOMATIC CLASSIFICATION OF MELANOMA SKIN CANCER WITH DEEP CONVOLUTIONAL NEURAL NETWORKS," Accepted at AI (MDPI), 2022.
-Y-h. Taguchi and Turki Turki, "Integrated Analysis of Tissue-specific Gene Expression in Diabetes by Tensor Decomposition Can Identify Possible Associated Diseases," Accepted at Genes, 2022. IF: 4.096.
-Y-h. Taguchi and Turki Turki, "Novel feature selection via kernel tensor decomposition for improved multi-omics data analysis," BMC Medical Genomics, 2022. IF: 3.063
-Turki Turki and Zhi Wei, "Improved Deep Convolutional Neural Networks via Boosting for Predicting the Quality of in Vitro Bovine Embryos,"  in Electronics (Medical Image Computing and Analysis Special Issue), 2022. IF: 2.397
-Y-h. Taguchi and Turki Turki, "Effects of the collagen–glycosaminoglycan mesh on gene expression as determined by using principal component analysis-based unsupervised feature extraction, " Polymers, 2021. IF: 4.329
-Y-h. Taguchi and Turki Turki, "Tensor-decomposition-based unsupervised feature extraction in single-cell multiomics data analysis, " Genes, 2021. IF: 4.096
-Xiang Lin, Jie Zhang, Zhi Wei, and Turki Turki,"An Omnibus Test for Differential Distribution Analysis of Continuous Microbiome Data," IEEE Access, 2021. IF: 3.367
-Turki Turki, Anmar Al-Sharif and Y-h. Taguchi, "End-to-End Deep Learning for Detecting Metastatic Breast Cancer in Axillary Lymph Node from Digital Pathology Images,"Accepted at IDEAL 2021.
-Y-h. Taguchi and Turki Turki, "Mathematical formulation and application of kernel tensor decomposition based unsupervised feature extraction," Accepted at Knowledge-Based Systems, 2021, Impact Factor: 8.038
-Y-h. Taguchi and Turki Turki, "Unsupervised tensor decomposition-based method to extract candidate transcription factors as histone modification bookmarks in post-mitotic transcriptional reactivation," Accepted at PLOS ONE, 2021.
-Turki Turki and Y-h. Taguchi, "Discriminating the Single-cell Gene Regulatory Networks of Human Pancreatic Islets: A Novel Deep Learning Application," Accepted at Computers in Biology and Medicine, 2021, IF: 4.589
-Y-h. Taguchi and Turki Turki, "Tensor decomposition based unsupervised feature extraction in big data analytics applied to prostate cancer multiomics data," Accepted at Genes, 2020. Impact Factor: 3.759
-Y-h. Taguchi and Turki Turki, "Universal nature of drug treatment responses in drug-tissue-wide model-animal experiments using tensor decomposition-based unsupervised feature extraction," Frontiers in Genetics, 2020. Impact Factor: 3.258
-Y-h. Taguchi and Turki Turki, “Application of Tensor Decomposition to Gene Expression of Infection of Mouse Hepatitis Virus can Identify Critical Human Genes and Efffective Drugs for SARS-CoV-2 Infection,” 2021, IEEE Journal on Selected Topics in Signal Processing. Impact Factor: 6.856
-Y-h. Taguchi and Turki Turki, “Novel Method for the Prediction of Drug–Drug Interactions Based on Gene Expression Profiles,” Accepted at European Journal of Pharmaceutical Sciences, 2021, Cite Score: 7.6
-Y-h. Taguchi and Turki Turki, “A New Advanced In Silico Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-Based Unsupervised Feature Extraction,” PLOS ONE, 2020, Impact Factor: 2.74
-Abdullah Algarni, Emad Kaen, Turki Turki, "New Machine Learning Approaches to Improve Software Bug Prediction," Accepted at International Conference on Machine Learning and Data Mining, 2020, New York.
-Zhihang Hu, Turki Turki, Jason T. L. Wang, "Generative Adversarial Networks for Stochastic Video Prediction with Action Control," IEEE Access, 2020. Impact Factor: 4.098
-Turki Turki and Y-h. Taguchi, "SCGRNs: Novel supervised inference of single-cell gene regulatory networks of complex diseases," Computers in Biology and Medicine, 2020. Impact Factor: 2.286
-Y-h. Taguchi and Turki Turki, "Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression Analysis," Frontiers in Genetics, 2019. Impact Factor: 3.517
-Y-h. Taguchi and Turki Turki, "Neurological disorder drug discovery from gene expression with tensor decomposition," Current Pharmaceutical Design, 2019. Impact Factor: 2.412
-Turki Turki and Y-h. Taguchi, "Machine Learning Algorithms for Predicting Drugs-Tissues Relationships," Accepted at Expert Systems with Applications, 2019. Impact Factor: 3.768
-Turki Turki and Jason T. L. Wang, "Clinical intelligence: New machine learning techniques for predicting clinical drug response," Computers in Biology and Medicine, 2019. Impact Factor: 2.115
-Haodi Jiang, Turki Turki and Jason T. L. Wang, "DLGraph: Malware Detection Using Deep Learning and Graph Embedding," Accepted at the 17th ICMLA, 2018.
-Turki Turki and Zhi Wei, "Boosting Support Vector Machines for Cancer Discrimination Tasks," Accepted at Computers in Biology and Medicine, 2018. Impact Factor: 2.115
-Z. Hu, T. Turki, N. Phan and J. T. L. Wang, "A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction," in IEEE Access, 2018. Impact Factor: 3.557
-Liulin Yang, Yun Li, Turki Turki, Huizi Tan, Zhi Wei and Xiao Chang, "Weighted Gene Co-Expression Network Analysis Reveals Dysregulation of Mitochondrial Oxidative Phosphorylation in Eating Disorders," Genes, 2018. Impact Factor: 3.191
-Haodi Jiang, Turki Turki, Sen Zhang and Jason T. L. Wang, "Reverse Engineering Gene Regulatory Networks Using Graph Mining," Accepted at the 14th International Conference on Machine Learning and Data Mining (MLDM 2018), July 13 - 18, 2018, New York, USA.
-Turki Turki, Zhi Wei, Jason T. L. Wang, "A Transfer Learning Approach via Procrustes Analysis and Mean Shift for Cancer Drug Sensitivity Prediction," Accepted at the Journal of Bioinformatics and Computational Biology (JBCB). Impact Factor: 0.800
-Turki Turki, "An Empirical Study of Machine Learning Algorithms for Cancer Identification," Accepted at the 15th IEEE International Conference on Networking, Sensing and Control (ICNSC 2018), Zhuhai, China, March 27-29, 2018.
-Haodi Jiang, Turki Turki, and Jason T. L. Wang, ”Reverse Engineering Regulatory Networks in Cells Using a Dynamic Bayesian Network and Mutual Information Scoring Function,” Accepted at the 16th IEEE International Conference on Machine Learning and Applications, Cancun, Mexico, December 18-21, 2017.
-Turki Turki, Zhi Wei, and Jason T. L. Wang, "A Transfer Learning Approach via Procrustes Analysis and Mean Shift for Cancer Drug Sensitivity Prediction," Accepted at the 28th International Conference on Genome Informatics Workshop (GIW) / BIOINFO 2017, Seoul, Korea, Oct 31-Nov 3, 2017.
-Turki Turki, Zhi Wei, and Jason T. L. Wang, “Transfer Learning Approaches to Improve Drug Sensitivity Prediction in Multiple Myeloma Patients,” Accepted at IEEE Access. Impact Factor: 3.224
-Turki Turki and Jason T. L. Wang, “Reverse Engineering Gene Regulatory Networks Using Sampling and Boosting Techniques,” Accepted at the 13th International Conference on Machine Learning and Data Mining, New York, NY, 2017.
-Yasser Abduallah, Turki Turki, Kevin Byron, Zongxuan Du, Miguel Cervantes-Cervantes, and Jason T. L. Wang, “MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach,” BioMed Research International, vol. 2017, Article ID 6261802, 8 pages, 2017. Impact Factor: 2.467
-Turki Turki and Zhi Wei, “A Noise-Filtering Approach for Cancer Drug Sensitivity Prediction,” in the Proceedings of the Neural Information Processing Systems Workshop on Machine Learning for Health (NIPS ML4HC), Barcelona, Spain, 2016.
-Turki Turki and Zhi Wei, “A Link Prediction Approach to Cancer Drug Sensitivity Prediction,” International Conference on Intelligent Biology and Medicine (ICIBM), Houston, Texas, USA, 2016. Accepted for inclusion as a special issue in BioMed Central (BMC) Systems Biology. Impact Factor: 2.303
-Turki Turki, Jason T. L. Wang, and Ibrahim Rajikhan, “Inferring Gene Regulatory Networks by Combining Supervised and Unsupervised Methods,” in the Proceedings of the 15th International Conference on Machine Learning and Applications (ICMLA), Anaheim, California, 2016.
-Turki Turki and Zhi Wei, “Learning Approaches to Improve Prediction of Drug Sensitivity in Breast Cancer Patients,” in the Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL, 2016.
-Turki Turki and Jason T. L. Wang, “A Learning Framework to Improve Unsupervised Gene Network Inference,” in the Proceedings of the 12th International Conference on Machine Learning and Data Mining, New York, NY, pp. 28-42, 2016.
-Turki Turki and Zhi Wei, “A Greedy-Based Oversampling Approach to Improve the Prediction of Mortality in MERS Patients,” in the Proceedings of the 10th Annual IEEE International Systems Conference, Orlando, FL, 2016.
-Turki Turki and Jason T. L. Wang, "A New Approach to Link Prediction in Gene Regulatory Networks," in the Proceedings of the 16th International Conference on Intelligent Data Engineering and Automated Learning, Wroclaw, Poland, 2015.
-Turki Turki and Zhi Wei, “IPRed: Instance Reduction Algorithm Based on the Percentile of the Partitions,” in the Proceedings of the 26th Modern AI and Cognitive Science Conference, Greensboro, NC, 2015.
-Turki Turki and Usman Roshan, "MaxSSmap: A GPU program for divergent short read mapping to genomes with the maximum scoring subsequence," BioMed Central Genomics (BMC Genomics), 2014. Impact Factor: 3.729.
-Turki Turki, Muhammad Amimul Ihsan, Nouf Turki, Jie Zhang, Usman Roshan and Zhi Wei, “Top-k Parametrized Boost,” in the Proceedings of the Second International Conference on Mining Intelligence and Knowledge Exploration, Cork, Ireland, 2014.
-Turki and Usman Roshan, “Weighted Maximum Variance Dimensionality Reduction,” in the Proceedings of the 6th Mexican Conference on Pattern Recognition, Cancun, Mexico, 2014