A5056364272- Bioinformatics and Genomic Networks
- Cancer-related molecular mechanisms research
- Gene expression and cancer classification
- RNA modifications and cancer
- Genomics and Phylogenetic Studies
- MicroRNA in disease regulation
- Machine Learning in Bioinformatics
- Computational Drug Discovery Methods
- Biomedical Text Mining and Ontologies
- Genomics and Rare Diseases
- Genomics and Chromatin Dynamics
- RNA Research and Splicing
- SARS-CoV-2 and COVID-19 Research
- Single-cell and spatial transcriptomics
- Metabolomics and Mass Spectrometry Studies
- Circular RNAs in diseases
- Genomic variations and chromosomal abnormalities
- RNA and protein synthesis mechanisms
- AI in cancer detection
- CRISPR and Genetic Engineering
- Plant Molecular Biology Research
- Genetic Mapping and Diversity in Plants and Animals
- Immune responses and vaccinations
- Genetic Associations and Epidemiology
- Protein Structure and Dynamics
Harbin Institute of Technology
2015-2024
Heilongjiang Institute of Technology
2013-2020
Indiana University – Purdue University Indianapolis
2013-2014
Indiana University School of Medicine
2013
Indiana University
2011
The identification of disease-related microRNAs is vital for understanding the pathogenesis diseases at molecular level, and critical designing specific tools diagnosis, treatment prevention. Experimental poses considerable difficulties. Computational analysis microRNA-disease associations an important complementary means prioritizing further experimental examination. Herein, we devised a computational model to infer potential by entire human microRNAome interest. We tested on 270 known...
Abstract SC2disease (http://easybioai.com/sc2disease/) is a manually curated database that aims to provide comprehensive and accurate resource of gene expression profiles in various cell types for different diseases. With the development single-cell RNA sequencing (scRNA-seq) technologies, uncovering cellular heterogeneity tissues diseases has become feasible by profiling transcriptomes across at level. In particular, comparing between identifying cell-type-specific genes offers new...
Abstract Background Over 10,000 long intergenic non-coding RNAs (lincRNAs) have been identified in the human genome. Some well characterized and known to participate various stages of gene regulation. In post-transcriptional process, another class well-known small RNA, or microRNA (miRNA), is very active inhibiting mRNA. Though similar features between mRNA lincRNA revealed several recent studies, a few isolated miRNA-lincRNA relationships observed. Despite these advances, comprehensive...
Single-cell RNA sequencing (scRNA-seq) detects whole transcriptome signals for large amounts of individual cells and is powerful determining cell-to-cell differences investigating the functional characteristics various cell types. scRNA-seq datasets are usually sparse highly noisy. Many steps in analysis workflow, including reasonable gene selection, clustering annotation, as well discovering underlying biological mechanisms from such datasets, difficult. In this study, we proposed an method...
In the cell nucleus, each chromosome is confined to a territory. This spatial organization of chromosomes plays crucial role in gene regulation and genome stability. An additional level has been discovered at scale: segregation into open closed chromatins form two genome-wide compartments. Although considerable progress made our knowledge chromatin organization, fundamental issue remains understanding its dynamics, especially cancer. To address this issue, we performed mapping interactions...
A microRNA is a small noncoding RNA molecule, which functions in silencing and posttranscriptional regulation of gene expression. To understand the mechanism activation genes, location promoter regions driving their expression required to be annotated precisely. Only fraction genes have confirmed transcription start sites (TSSs), hinders our understanding factor binding events. With development next generation sequencing technology, chromatin states can inferred precisely by virtue...
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing an outbreak of disease 2019 (COVID-19), has been undergoing various mutations. The analysis the structural and energetic effects mutations on protein-protein interactions between receptor binding domain (RBD) SARS-CoV-2 angiotensin converting enzyme (ACE2) or neutralizing monoclonal antibodies will be beneficial for epidemic surveillance, diagnosis, optimization agents. According to molecular dynamics simulation, a key...
Abstract Background The Gene Ontology (GO) has been used in high-throughput omics research as a major bioinformatics resource. hierarchical structure of GO provides users convenient platform for biological information abstraction and hypothesis testing. Computational methods have developed to identify functionally similar genes. However, none the existing measurements take into account all rich GO. Similarly, using these methods, web-based applications constructed compute gene functional...
Abstract Background RNA-binding proteins (RBPs) play diverse roles in eukaryotic RNA processing. Despite their pervasive functions coding and noncoding biogenesis regulation, elucidating the sequence specificities that define protein-RNA interactions remains a major challenge. Recently, CLIP-seq (Cross-linking immunoprecipitation followed by high-throughput sequencing) has been successfully implemented to study transcriptome-wide binding patterns of SRSF1, PTBP1, NOVA fox2 proteins. These...
Fungal pathogens have evolved the ability to cause serious plant diseases and threaten world food security. effectors are proteins that exploit host cellular functions facilitate infection. Effector identification is crucial for disease control in crops understand plant-pathogen interactions. However, fungal effector has been challenging as most lack of consensus motifs data imbalance problem. In this study, a predictor was designed effectively learn from an imbalanced dataset. A granular...
Understanding how genetic variants influence molecular phenotypes in different cellular contexts is crucial for elucidating the and mechanisms behind complex traits, which turn has spurred significant advances research into quantitative trait locus (xQTL) at level. With rapid proliferation of data, there a critical need comprehensive accessible platform to integrate this information. To meet need, we developed xQTLatlas (http://www.hitxqtl.org.cn/), database that provides multi-omics...
Bidirectional promoters are shared promoter sequences between divergent gene pair (genes proximal to each other on opposite strands), and can regulate the genes in both directions. In human genome, > 10% of protein-coding arranged head-to-head strands, with transcription start sites that separated by < 1,000 base pairs. Many factor binding occur bidirectional influence expression 2 genes. Recently, RNA polymerase II (RPol II) ChIP-seq data used identify coding non-coding RNAs. However, a...
Whole genome sequencing (WGS) of parent-offspring trios is a powerful approach for identifying disease-associated genes via detecting copy number variations (CNVs). Existing approaches, which detect CNVs each individual in trio independently, usually yield low-detection accuracy. Joint modeling approaches leveraging Mendelian transmission within the can be an efficient strategy to improve CNV detection accuracy.In this study, we developed TrioCNV, novel jointly from WGS data. Using negative...
Abstract Background Over the past decades, a large number of long non-coding RNAs (lncRNAs) have been identified. Growing evidence has indicated that mutation and dysregulation lncRNAs play critical role in development many complex human diseases. Consequently, identifying potential disease-related is an effective means to improve quality disease diagnostics treatment, which motivation this work. Here, we propose computational model (LncDisAP) for lncRNA identification based on multiple...
ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing an outbreak of disease 2019 (COVID-19), has been undergoing various mutations. The analysis the structural and energetic effects mutations on protein-protein interactions between receptor binding domain (RBD) SARS-CoV-2 angiotensin converting enzyme (ACE2) or neutralizing monoclonal antibodies will be beneficial for epidemic surveillance, diagnosis, optimization agents. According to molecular dynamics simulation,...
Enzymes are proteins that can efficiently catalyze specific biochemical reactions, and they widely present in the human body. Developing an efficient method to identify enzymes is vital select from vast number of investigate their functions. Nevertheless, only a limited amount research has been conducted on classification nonenzymes. In this work, we developed support vector machine- (SVM-) based predictor classify using amino acid composition (AAC), <mml:math...
Gastric cancer (GS) is the fourth most common malignant tumor. The mechanism underlying GS occurrence and development remains unclear. Previous studies have indicated that long noncoding RNAs (lncRNAs) are significantly associated with gastric cancer, but a systematic understanding of role lncRNAs in lacking. In recent years, next-generation sequencing technology, tens thousands been discovered. However, large number unannotated remain unidentified different tissues, including potential...
Discovering similar diseases is very helpful for revealing the pathogenesis of and making direction in drug use. And related are often triggered by disease-related genes. Therefore, function interaction networks structured genes suitable measurement disease similarity, some methods have utilized advantage However, all them were developed using a single gene functional network, ignoring effect non-neighbour nodes network. In this study, we propose new method, FNSemSim, computing relatedness...
Abstract Background As the terminal products of cellular regulatory process, functional related metabolites have a close relationship with complex diseases, and are often associated same or similar diseases. Therefore, identification disease play critical role in understanding comprehensively pathogenesis disease, aiming at improving clinical medicine. Considering that large number metabolic markers diseases need to be explored, we propose computational model identify potential...
Advances in high-throughput sequencing technologies have brought us into the individual genome era. Projects such as 1000 Genomes Project led to become more and popular. How visualize, analyse annotate genomes with knowledge bases support studies personalized healthcare is still a big challenge. The Personal Genome Browser (PGB) developed provide comprehensive functional annotation visualization for based on genetic–molecular–phenotypic model. Investigators can easily view genetic variants,...
Abstract Background In biological systems, metabolomics can not only contribute to the discovery of metabolic signatures for disease diagnosis, but is very helpful illustrate underlying molecular disease-causing mechanism. Therefore, identification disease-related metabolites great significance comprehensively understanding pathogenesis diseases and improving clinical medicine. Results paper, we propose a literature driven metabolism prediction model (DLMPM) identify potential associations...