Guest Editors
Saurav Mallik
University of Arizona, Tucson, AZ, USA
Dr. Saurav Mallik is currently working as Research Scientist in the Department of Pharmacology and Toxicology, The University of Arizona, USA. Previously, he worked as Postdoctoral Fellow in the Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, USA for more than three years (2019-2022), the Center of Precision Health, Department of School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA for one and half year (2018-2019), and in the Division of Bio-statistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA for more than one year (2017-2018). He obtained his PhD degree in the Department of Computer Science & Engineering (C.S.E.) from Jadavpur University, Kolkata, India in 2017 while his PhD works carried out in Machine Intelligence Unit (MIU), Indian Statistical Institute (ISI), Kolkata, India. He worked previously at ISI, Kolkata, India as a Junior Research Fellow (JRF) in DST (Department of Science & Technology, New Delhi, Govt. of India)-sponsored Swarnajayanti project and as a Visiting Scientist (VS) for a total of more than 3 years (2011-2013 & 2015-2016). He also worked in the Department of Computer Science & Engineering, Jadavpur University, Kolkata, India as UGC (University Grant Commission, Govt. of India) Research Fellow for 2 years (2014-2015 & 2016-2017). He is the recipient of Research Associate-ship (RA) from CSIR (Council of Scientific and Industrial Research), MHRD, Govt. of India in 2017. He also worked as assistant professor in the Department of Computer Science & Engineering in Mallabhum Institute of Technology, Bisnupur, WB, India (currently on leave). He is also recipient of "Emerging Researcher In Bioinformatics" award from Bioclues & BIRD Award steering committee, India (http://bioclues.org/) in the year 2020 and "Young scientist award" on “International Scientist Awards on Engineering, Science and Medicine" (ISAO 2021) from a non-profit organization, VDGOOD Professional Association of Scientists, Engineers and Doctors, India in the year 2021. His research areas include data mining, computational biology, bioinformatics, biostatistics and machine learning.
Nanda Dulal Jana
National Institute of Technology Durgapur, India
Dr. Nanda Dulal Jana completed his B.Sc. in Mathematics (Hons), B. Tech and M. Tech in Computer Science & Engineering from University of Calcutta, India in 2001, 2004 and 2006. He received PhD from Computer Science Technology Department of IIEST Shibpur, India in 2017. He is currently serving as an Assistant Professor in Computer Science & Engineering Department of National Institute of Technology Durgapur. He has authored/co-authored more than 40 technical articles in journals and international conferences. Dr. Jana’s key research interests include Metaheuristic Optimization Techniques, Evolutionary Machine Learning, Deep Learning and their applications to Protein Structure Prediction, Computer Aided Drug Design, Image Classifications, EEG Signal Classifications and Speech Synthesizes.
Mingqiang Wang
Stanford University, Stanford, CA, USA
Dr. Mingqiang Wang is currently working as Postdoctoral Fellow in Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA. He completed his M.Sc from Chinese Academy Of Sciences in 2015 and PhD. from Chinese University of Hong Kong in 2018. Dr. Wang has more than 20 research publications in various top high impact factor peer-reviewed International Journals, Conferences and Book Chapters. He has also worked as guest editors and reviewers with several well-reputed high impact journals. His research areas include Computational Biology, Bioinformatics and Molecular Informatics.
Mufti Mahmud
Nottingham Trent University, Clifton Lane, NG11 8NS, Nottingham, United Kingdom
Dr. Mufti Mahmud is an Associate Professor of Cognitive Computing at the Department of Computer Science of Nottingham Trent University (NTU). Dr Mahmud was appointed to the USET, University Shadow Executive Team, in 2022, providing specialist input to the University Executive Team and Vice-Chancellor on strategic policy and direction matters related to Equality, Diversity & Inclusion (EDI). Particularly, he shadows the Pro Vice-Chancellor (Research and Innovation) in matters related to the development of the research environment at NTU and its five strategic research themes from the EDI viewpoint. He is the Coordinator of the Computer Science and Informatics (B11) Unit of Assessment of Research Excellence Framework at NTU and the deputy group leader of the Interactive Systems Research Group (ISRG) and the Cognitive Computing & Brain Informatics (CCBI) research group. He is also an active member of the Computing and Informatics Research Centre (CIRC) and the Medical Technologies Innovation Facility (MTIF). He is a member of the NTU Distance Learning Governance, Operation and Steering committee as well as the International Mobility Committee and serves as an independent end-point assessor for the Level 6 BSc (Hons) in Digital & Technology Solutions Professional Degree Apprenticeship, and an expert of the online master's degree in computer science. He led the teaching of the Big Data and its Infrastructures (Postgraduate – on-campus and online delivery) module. He is a Fellow of the Higher Education Academy, a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association of Computing Machinery (ACM), and a professional member of the British Computer Society (BCS).
Kanad Ray
Amity School of Applied Sciences, Amity University Rajasthan, Kant Kalwar, NH-11C, Jaipur, India
Prof. (Dr.) Kanad Ray is currently working as professor in the Department of Physics & Electronics and Communication in Amity School of Applied Sciences, Amity University Rajasthan, Kant Kalwar, NH-11C, Jaipur, India. He has authored/co-authored more than 90 peer-reviewed publications in international journals and international conferences. His research areas include bio-electromagnetics, communication, cognition and consciousness.
Priyanka Roy
Vellore Institute of Technology (VIT) Bhopal University, India
Dr. Priyanka Roy completed her B.Sc in Mathematics (Hons) from University of Calcutta, India in 2012, M.Sc. and PhD. both in the Department of Mathematics from Indian Institute of Technology Kharagpur in 2014 and 2022. He is currently serving as an Assistant Professor in Department of Mathematics Division, School of Advanced Sciences and Languages, Vellore Institute of Technology (VIT) Bhopal University, India. She has authored/co-authored more than 36 peer-reviewed publications in international journals and international conferences. Her research areas include Continuous Optimization, Numerical Optimization, Generalized Convexity, Interval Analysis, Optimization under Uncertainty, Nonlinear Programming, Uncertainty Quantification, Mathematical Analysis, Numerical Algorithm, Numerical Linear Algebra and Portfolio Optimization.
Collection Overview
In this era, multi-disciplinary research has greatly impacted various biomedical and health-related challenges, particularly those related to medical imaging, high-throughput next-generation sequencing, and EEG/ECG signal processing data analysis. This approach has played an essential role in computer-added clinical decision support systems that allow in-depth but non-invasive explanations of internal anatomy. The technological shift has enhanced healthcare efficacy, including complex disease detection, disease subtype identification, treatment methodologies and quantitative self-monitoring. The recent increase in computational power and resources has enabled the development of new technologies/frameworks that utilize well-established modalities. Advancements in artificial intelligence (AI), machine learning (ML), deep learning (DL), artificial neural network (ANN) and optimization methods have become prevalent across various aspects of biomedical imaging, RNAseq data analysis, single-cell data analysis as well as bioinspired signaling data study for the identification of complex disease patterns and potential therapeutics. In addition, the appropriate utilization of ML, DL, ANN, optimization, and signal processing techniques has been integrated to investigate and resolve numerous real-world challenges.
This Methods Collection aims to cover recent advances and applications of ML, DL, ANN, and optimization techniques towards biomedical imaging, next-generation sequencing data and biosensor analysis. We mainly focus on reviews and novel theories, algorithms, and applications. The topic of interest includes, but is not limited to:
- ML, DL, ANN and optimization techniques on RNAseq, microarray, and single-cell sequencing data for disease detection.
- Matrix factorization-based methods in multi-omics data analysis.
- Hub gene finding, gene signature detection, and gene module discovery for genomic and epigenomic data.
- Methodologies of feature extraction and feature selection in next-generation sequencing and medical image analysis.
- Multi-modal data fusion for array-based sequence data as well as biomedical imaging.
- Theory of Intelligent computing methods for medical image analysis.
- Application of swarm-based algorithms and metaheuristics for medical image analysis.
- Multi-objective and hybrid approaches for medical image analysis.
- Model-based computing algorithm for medical image analysis.
- Automated ML and DL for medical image and EEG/ECG signaling data analysis.
- Applications in medical imaging, acquisition, reconstruction, segmentation, registration, detection, tracking, etc.
- ML, ANN, DL and signal processing in biosensors and bioelectronics for biomedical informatics and healthcare services.
- ML, DL, ANN, and signal processing for human motion monitoring and related systems.
- ML, DL, ANN in audio, speech, and natural language processing (NLP) for healthcare and biomedical security systems.