Data Science and Modeling in Biology, Health, and Medicine

Submission Deadline: 31 March 2020 (closed) View: 162

Guest Editors

Prof. Ka-Chun Wong, City University of Hong Kong, Hong Kong SAR
Prof. Xiangtao Li, Northeast Normal University, China
Dr. Frederick Kin Hing Phoa, Academia Sinica, Taiwan

Summary

Since the 2010s, the high-throughput sequencing technologies such as Oxford Nanopore sequencing and other third-generation sequencing facilities have revolutionized the molecular biology research field. Such an advancement has propelled a multitude of downstream studies lead to significant impacts on biology, health, and medicine. However, such kind of new data is big, fast, and heterogeneous. It demands a new set of data science and modeling approaches in terms of computational scalability, complexity, and fault-tolerance.

Therefore, we have initiated such a special issue on the data science and modeling in biology, health, and medicine in the hope that researchers can gather their works together in a single special issue for broad and deep impacts on multiple disciplines such as mathematical biology, bioinformatics, computational biology, health informatics, biomedical engineering, cancer informatics, translational medicine, and other related fields.

Keywords

Bioinformatics; Computational Biology; Machine Learning; Data Science; Data Mining; Computational Intelligence; Natural Computing; Genetic Algorithm; Differential Evolution; Evolutionary Computation

Published Papers

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Open Access

ARTICLE

Exploring the Abnormal Brain Regions and Abnormal Functional Connections in SZ by Multiple Hypothesis Testing Techniques
Lan Yang, Shun Qi, Chen Qiao, Yanmei Kang
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 215-237, 2020, DOI:10.32604/cmes.2020.010796
（This article belongs to the Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both… More >

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ARTICLE

Fractional-Order Model for Multi-Drug Antimicrobial Resistance
M. F. Elettreby, Ali S. Alqahtani, E. Ahmed
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 665-682, 2020, DOI:10.32604/cmes.2020.09194
（This article belongs to the Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract Drug resistance is one of the most serious phenomena in financial, economic and medical terms. The present paper proposes and investigates a simple mathematical fractional-order model for the phenomenon of multi-drug antimicrobial resistance. The model describes the dynamics of the susceptible and three kinds of infected populations. The first class of the infected society responds to the first antimicrobial drug but resists to the second one. The second infected individuals react to the second antimicrobial drug but resist to the first one. The third class shows resistance to both of the two drugs. We formulate More >

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ARTICLE

Effect of Absorption of Patch Antenna Signals on Increasing the Head Temperature
Mohamed Abbas, Ali Algahtani, Amir Kessentini, Hassen Loukil, Muneer Parayangat, Thafasal Ijyas, Abdul Wase Mohammed
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 683-701, 2020, DOI:10.32604/cmes.2020.010304
（This article belongs to the Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract Every new generation of antennas is characterized by increased accuracy and faster transmission speeds. However, patch antennas have been known to damage human health. This type of antenna sends out electromagnetic waves that increase the temperature of the human head and prevent nerve strands from functioning properly. This paper examines the effect of the communication between the patch antenna and the brain on the head’s temperature by developing a hypothetical multi-input model that achieves more accurate results. These inputs are an individual’s blood and tissue, and the emission power of the antenna. These forces depend… More >

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2223
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ARTICLE

A Re-Parametrization-Based Bayesian Differential Analysis Algorithm for Gene Regulatory Networks Modeled with Structural Equation Models
Yan Li, Dayou Liu, Yungang Zhu, Jie Liu
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 303-313, 2020, DOI:10.32604/cmes.2020.09353
（This article belongs to the Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract Under different conditions, gene regulatory networks (GRNs) of the same gene set could be similar but different. The differential analysis of GRNs under different conditions is important for understanding condition-specific gene regulatory relationships. In a naive approach, existing GRN inference algorithms can be used to separately estimate two GRNs under different conditions and identify the differences between them. However, in this way, the similarities between the pairwise GRNs are not taken into account. Several joint differential analysis algorithms have been proposed recently, which were proved to outperform the naive approach apparently. In this paper, we… More >

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ARTICLE

Discrete Circular Distributions with Applications to Shared Orthologs of Paired Circular Genomes
Tomoaki Imoto, Grace S. Shieh, Kunio Shimizu
CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1131-1149, 2020, DOI:10.32604/cmes.2020.08466
（This article belongs to the Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract For structural comparisons of paired prokaryotic genomes, an important topic in synthetic and evolutionary biology, the locations of shared orthologous genes (henceforth orthologs) are observed as binned data. This and other data, e.g., wind directions recorded at monitoring sites and intensive care unit arrival times on the 24-hour clock, are counted in binned circular arcs, thus modeling them by discrete circular distributions (DCDs) is required. We propose a novel method to construct a DCD from a base continuous circular distribution (CCD). The probability mass function is defined to take the normalized values of the probability… More >

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ARTICLE

Growing and Pruning Based Deep Neural Networks Modeling for Effective Parkinson’s Disease Diagnosis
Kemal Akyol
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 619-632, 2020, DOI:10.32604/cmes.2020.07632
（This article belongs to the Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract Parkinson’s disease is a serious disease that causes death. Recently, a new dataset has been introduced on this disease. The aim of this study is to improve the predictive performance of the model designed for Parkinson’s disease diagnosis. By and large, original DNN models were designed by using specific or random number of neurons and layers. This study analyzed the effects of parameters, i.e., neuron number and activation function on the model performance based on growing and pruning approach. In other words, this study addressed the optimum hidden layer and neuron numbers and ideal activation More >

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Data Science and Modeling in Biology, Health, and Medicine

Guest Editors

Summary

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Published Papers

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2546

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1781

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2935

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2225

Cited by

2

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3060

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2223

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3184

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2700

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3533

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2179

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3805

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2372

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