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Traditional Chinese Medicine (TCM) has the longest clinical history in Asia and contributes a lot to health maintenance worldwide. An essential step during the TCM diagnostic process is syndrome induction, which comprehensively analyzes the symptoms and ...

Drug repositioning/repurposing is a very important approach towards identifying novel treatments for diseases in drug discovery. Recently, large-scale biological datasets are increasingly available for pharmaceutical research and promote the development ...

Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great importance and urgency during the worldwide outbreak. However, radiologists have to distinguish COVID-19 pneumonia from other pneumonia in a large number ...

Aptamers are short, single-stranded oligonucleotides or peptides generated from in vitro selection to selectively bind with various molecules. Due to their molecular recognition capability for proteins, aptamers are becoming promising reagents in new drug ...

One of the key challenges in systems biology is to derive gene regulatory networks (GRNs) from complex high-dimensional sparse data. Bayesian networks (BNs) and dynamic Bayesian networks (DBNs) have been widely applied to infer GRNs from gene expression ...

Ensemble methods such as random forest works well on high-dimensional datasets. However, when the number of features is extremely large compared to the number of samples and the percentage of truly informative feature is very small, performance of ...

Amyotrophic Lateral Sclerosis is a devastating neurodegenerative disease causing rapid degeneration of motor neurons and usually leading to death by respiratory failure. Since there is no cure, treatment’s goal is to improve symptoms and prolong ...

Foot-and-mouth disease virus (FMDV) is an antigenic-variable RNA virus that is responsible for the recurrence of foot-and-mouth disease in livestock and can be prevented and controlled using a vaccine with broad-spectrum protection. Current anti-genicity ...

Drug repurposing is a vital function in pharmaceutical fields and has gained popularity in recent years in both the pharmaceutical industry and research community. It refers to the process of discovering new uses and indications for existing or failed ...

Computational drug repositioning, which is an efficient approach to find potential indications for drugs, has been used to increase the efficiency of drug development. The drug repositioning problem essentially is a top-K recommendation task that ...

Ab initio protein structure prediction is one of the most challenging problems in computational biology. Multistage algorithms are widely used in ab initio protein structure prediction. The different computational costs of a multistage algorithm for ...

Single nucleotide polymorphisms (SNPs) are one type of genetic variations and each SNP represents a difference in a single DNA building block, namely a nucleotide. Previous research demonstrated that SNPs can be used to identify the correct source ...

Protein phosphorylation is one of the key mechanism in prokaryotes and eukaryotes and is responsible for various biological functions such as protein degradation, intracellular localization, the multitude of cellular processes, molecular association, ...

Mitosis detection is one of the challenging steps in biomedical imaging research, which can be used to observe the cell behavior. Most of the already existing methods that are applied in detecting mitosis usually contain many nonmitotic events (normal ...

The eight papers in this special section focus on novel theories and methods using transfer learning proposed for medical imaging and health information processes.

Higher-resolution biopsy slice images reveal many details, which are widely used in medical practice. However, taking high-resolution slice images is more costly than taking low-resolution ones. In this paper, we propose a joint framework containing a ...

Conventional classification models for epileptic EEG signal recognition need sufficient labeled samples as training dataset. In addition, when training and testing EEG signal samples are collected from different distributions, for example, due to ...

Recently, coronary heart disease has attracted more and more attention, where segmentation and analysis for vascular lumen contour are helpful for treatment. And intravascular optical coherence tomography (IVOCT) images are used to display lumen shapes in ...

Traditional clustering algorithms for medical image segmentation can only achieve satisfactory clustering performance under relatively ideal conditions, in which there is adequate data from the same distribution, and the data is rarely disturbed by noise ...

One type of cancer usually consists of several subtypes with distinct clinical implications, thus the cancer subtype prediction is an important task in disease diagnosis and therapy. Utilizing one type of data from molecular layers in biological system to ...