Zhi-An Huang

City University of Hong Kong | CityU · Department of Computer Science

Facing the prevalence of mental disorders around the world, the burden of healthcare services becomes increasingly imminent. To lessen patients' suffering, the timely diagnosis and therapy of mental disorders are particularly essential. Functional magnetic resonance imaging (fMRI), as the de facto non-invasive neuroimaging technique, can effectivel...

Motivation: The interactions between T-cell receptors (TCR) and peptide-major histocompatibility complex (pMHC) are essential for the adaptive immune system. However, identifying these interactions can be challenging due to the limited availability of experimental data, sequence data heterogeneity, and high experimental validation costs. Results:...

The high prevalence of mental disorders gradually poses a huge pressure on the public healthcare services. Deep learning-based computer-aided diagnosis (CAD) has emerged to relieve the tension in healthcare institutions by detecting abnormal neuroimaging-derived phenotypes. However, training deep learning models relies on sufficient annotated datas...

Neuroimaging techniques have been widely adopted to detect the neurological brain structures and functions of the nervous system. As an effective noninvasive neuroimaging technique, functional magnetic resonance imaging (fMRI) has been extensively used in computer-aided diagnosis (CAD) of mental disorders, e.g., autism spectrum disorder (ASD) and a...

Underlying medical conditions, such as cancer, kidney disease and heart failure, are associated with a higher risk for severe COVID-19. Accurate classification of COVID-19 patients with underlying medical conditions is critical for personalized treatment decision and prognosis estimation. In this study, we propose an interpretable artificial intell...

The offloading of computation-intensive tasks to an edge server near resource-constrained mobile devices can provide improved application performance and user experience. However, with the rapid growth of mobile devices connected to the edge server, it is challenging to directly obtain an optimal task offloading scheme due to increasing computation...

Facing the increasing worldwide prevalence of mental disorders, the symptom-based diagnostic criteria struggle to address the urgent public health concern due to the global shortfall in well-qualified professionals. Thanks to the recent advances in neuroimaging techniques, functional magnetic resonance imaging (fMRI) has surfaced as a new solution...

The globally rising prevalence of mental disorders leads to shortfalls in timely diagnosis and therapy to reduce patients’ suffering. Facing such an urgent public health problem, professional efforts based on symptom criteria are seriously overstretched. Recently, the successful applications of computer-aided diagnosis approaches have provided time...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective: Deep learning (DL) techniques have been introduced to assist doctors in the interpretation of medical images by detecting image-derived phenotype abnormality. Yet the privacy-preserving policy of medical images disables the effective trainin...

Motivation The associations between biomarkers and human diseases play a key role in understanding complex pathology and developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious and time-consuming. Computational prediction methods can be used to greatly expedite the identification of candidate biomarkers. Re...

Background Recent evidences have suggested that human microorganisms participate in important biological activities in the human body. The dysfunction of host-microbiota interactions could lead to complex human disorders. The knowledge on host-microbiota interactions can provide valuable insights into understanding the pathological mechanism of dis...

Recently, the serious impairments of ASD cause a series of pending issues to increase a major burden of health and finance globally. In this work, we propose an effective convolutional neural network (CNN) - based model to identify the potential autistic risk genes based on the developmental brain gene expression profiles. Based on the 10-fold cros...

As a group of complex neurodevelopmental disorders, autism spectrum disorder (ASD) has been reported to have a high overall prevalence, showing an unprecedented spurt since 2000. Due to the unclear pathomechanism of ASD, it is challenging to diagnose individuals with ASD merely based on clinical observations. Without additional support of biochemic...

With the increasing prevalence of autism spectrum disorder (ASD), it is important to identify ASD patients for effective treatment and intervention, especially in early childhood. Neuroimaging techniques have been used to characterize the complex biomarkers based on the functional connectivity anomalies in the ASD. However, the diagnosis of ASD sti...

Motivation: Identifying microRNAs that are associated with different diseases as biomarkers is a problem of great medical significance. Existing computational methods for uncovering such microRNA-diseases associations (MDAs) are mostly developed under the assumption that similar microRNAs tend to associate with similar diseases. Since such an assu...

The interaction of miRNA and lncRNA is known to be important for gene regulations. However, the number of known lncRNA-miRNA interactions is still very limited and there are limited computational tools available for predicting new ones. Considering that lncRNAs and miRNAs share internal patterns in the partnership between each other, the underlying...

Clinical observations show that human microorganisms get involved in various human biological processes. The disruption of a symbiotic balance for host-microbiota relationship is found to cause different types of human complex diseases. Discoverying the associations between microbes and the host health statuses that they affect could provide great...

From transcriptional noise to dark matter of biology, the rapidly changing view of long non-coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by abnormal expression of lncRNAs. There is urgent need to discern potential functional roles of lncRNAs for further study of pathology, diagnosis, therapy, prognosis, preventi...

Background Current knowledge and data on miRNA-lncRNA interactions is still limited and little effort has been made to predict target lncRNAs of miRNAs. Accumulating evidences suggest that the interaction patterns between lncRNAs and miRNAs are closely related to relative expression level, forming a titration mechanism. It could provide an effectiv...

Background MicroRNA (miRNA) plays a key role in regulation mechanism of human biological processes, including the development of disease and disorder. It is necessary to identify potential miRNA biomarkers for various human diseases. Computational prediction model is expected to accelerate the process of identification. Results Considering the lim...

Background Accumulating clinical researches have shown that specific microbes with abnormal levels are closely associated with the development of various human diseases. Knowledge of microbe–disease associations can provide valuable insights for complex disease mechanism understanding as well as the prevention, diagnosis and treatment of various di...

An increasing number of evidences indicate microbes are implicated in human physiological mechanisms, including complicated disease pathology. Some microbes have been demonstrated to be associated with diverse important human diseases or disorders. Through investigating these disease-related microbes, we can obtain a better understanding of human d...

MicroRNA has become a new star molecule for understanding multiple biological processes and the mechanism of various complex human diseases. Even though a number of computational models have been proposed for predicting the association between microRNAs and various human diseases, most of them are mainly based on microRNA functional similarity and...

In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potenti...

Known human miRNA-disease associations obtained from HMDD database. (XLSX)

Names of 383 diseases involved in known human miRNA-disease associations obtained from HMDD database. (XLSX)

The constructed miRNA functional similarity score matrix. (XLSX)

PBMDA’s top-50 prediction list verified by dbDEMC and miR2Disease databases. (XLSX)

As a global measure model, PBMDA can simultaneously prioritize all unknown potential related miRNAs for all investigated diseases. We here publicly released the top-100 potential miRNA-disease associations predicted by PBMDA. (XLSX)

Names of 495 miRNAs involved in known human miRNA-disease associations obtained from HMDD database. (XLSX)

Background The rapid progress of high-throughput DNA sequencing techniques has dramatically reduced the costs of whole genome sequencing, which leads to revolutionary advances in gene industry. The explosively increasing volume of raw data outpaces the decreasing disk cost and the storage of huge sequencing data has become a bottleneck of downstrea...

With the advance of sequencing technology and microbiology, the microorganisms have been found to be closely related to various important human diseases. The increasing identification of human microbe-disease associations offers important insights into the underlying disease mechanism understanding from the perspective of human microbes, which are...