Junpeng Zhang

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Verified

Junpeng verified their affiliation via an institutional email.

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• Doctor of Engineering
• Professor at Dali University

Long COVID, also referred to as post-acute sequelae of COVID-19 (PASC), is a substantial global health concern estimated to have affected over 145 million individuals worldwide. Characterized by persistent and new symptoms extending beyond four weeks from the initial infection–such as fatigue, breathlessness, and cognitive impairments–Long COVID po...

Background: Long COVID, or Post–Acute Sequelae of COVID–19 (PASC), involves persistent, multisystemic symptoms in about 10–20% of COVID-19 patients. Although age, sex, ethnicity, and comorbidities are recognized as risk factors, identifying genetic contributors is essential for developing targeted therapies. Methods: We developed a multi–omics fram...

The homeotic transformation of stamens into pistil-like structures (pistillody) causes cytoplasmic male sterility (CMS). This phenomenon is widely present in plants, and might be induced by intracellular communication (mitochondrial retrograde signaling), but its systemic regulating mechanism is still unclear. In this study, morphological observati...

Cancer seriously threatens human life and health, and the structure and function of genes within cancer cells have changed relative to normal cells. Essentially, cancer is a polygenic disorder, and the core of its occurrence and development is caused by polygenic synergy. Non-coding RNAs (ncRNAs) act as regulators to modulate gene expression levels...

研究药物分子与靶标蛋白结合亲和力有助于了解生物系统和辅助药物开发。随着生物大数据驱动下的计算生物学技术发展，药物分子与靶标蛋白结合亲和力研究策略从传统单一生物医学实验迈向综合计算技术辅助预测，为药物开发提供新技术新方法。鉴于药物分子与靶标蛋白结合亲和力研究的重要性，从传统生物实验方法和计算生物学方法两个维度对其研究进展进行综述，重点介绍了预测药物分子与靶标蛋白结合亲和力的分子计算模拟、传统机器学习和深度学习方法，并阐述了每种计算生物学方法的应用场景、特点、优势和不足。最后，讨论了药物分子与靶标蛋白结合亲和力预测算法存在的问题以及未来方向，旨在为开发高性能药物分子与靶标蛋白结合亲和力预测模型提供参考。

Personalized cancer treatment strategies (PCTS) tailor treatments on the basis of a patient’s health status, cancer type, and stage. By considering the evolving interactions of treatment options over time, PCTS seeks to balance cancer suppression with minimizing harm and maximizing therapeutic benefits. However, limited clinical trial resources lim...

Background Autism spectrum disorder (ASD) is a class of complex neurodevelopment disorders with high genetic heterogeneity. Long non-coding RNAs (lncRNAs) are vital regulators that perform specific functions within diverse cell types and play pivotal roles in neurological diseases including ASD. Therefore, exploring lncRNA regulation would contribu...

Background RNA-sequencing technology provides an effective tool for understanding miRNA regulation in complex human diseases, including cancers. A large number of computational methods have been developed to make use of bulk and single-cell RNA-sequencing data to identify miRNA regulations at the resolution of multiple samples (i.e. group of cells...

MicroRNA (miRNA) sponges synergistically modulate physiological and pathological processes in the form of modules or clusters. Here, we present a protocol for inferring and analyzing miRNA sponge modules in heterogeneous data using the R package miRSM 2.0. We describe steps for identifying gene modules, inferring miRNA sponge modules at multi-sampl...

Promoters are important cis-regulatory elements for the regulation of gene expression, and their accurate predictions are crucial for elucidating the biological functions and potential mechanisms of genes. Many previous prokaryotic promoter prediction methods are encouraging in terms of the prediction performance, but most of them focus on the reco...

Autism spectrum disorder (ASD) is a class of complex neurodevelopment disorders with high genetic heterogeneity. Long non-coding RNAs (lncRNAs) are vital regulators that perform specific functions within diverse cell types and play pivotal roles in neurological diseases including ASD. Therefore, studying the specific regulation of lncRNAs in variou...

Polyphenol oxidases (PPOs) are type-3 copper enzymes and are involved in many biological processes. However, the potential functions of PPOs in pollination are not fully understood. In this work, we have screened 13 PPO members in Nicotiana. tabacum (named NtPPO1-13, NtPPOs) to explore their characteristics and functions in pollination. The results...

Promoters are important cis-regulatory elements for the regulation of gene expression, and their accurate predictions are crucial for elucidating the biological functions and potential mechanisms of genes. Many previous prokaryotic promoter prediction methods are encouraging in terms of the prediction performance, but most of them focus on the reco...

Non-coding RNAs (ncRNAs) act as important modulators of gene expression and they have been confirmed to play critical roles in the physiology and development of malignant tumors. Understanding the synergism of multiple ncRNAs in competing endogenous RNA (ceRNA) regulation can provide important insights into the mechanisms of malignant tumors caused...

RNA-sequencing technology provides an effective tool for understanding miRNA regulation in complex human diseases, including cancers. A large number of computational methods have been developed to make use of bulk and single-cell RNA-sequencing data to identify miRNA regulations at the resolution of multiple samples (i.e. group of cells or tissues)...

Non-coding RNAs (ncRNAs) act as important modulators of gene expression and they have been confirmed to play critical roles in the physiology and development of malignant tumors. Understanding the synergism of multiple ncRNAs in competing endogenous RNA (ceRNA) regulation can provide important insights into the mechanisms of malignant tumors caused...

Noncoding RNAs (ncRNAs) occupy ~98% of the transcriptome in human, and are usually not translated into proteins. Among ncRNAs, long non-coding RNAs (lncRNAs, >200 nucleotides) are important regulators to modulate gene expression, and are involved in many biological processes (e.g., cell development). To study lncRNA regulation, many computational a...

Long non-coding RNAs (lncRNAs) are important regulators to modulate gene expression and cell proliferation in the developing human brain. Previous methods mainly use bulk lncRNA and mRNA expression data to study lncRNA regulation. However, to analyze lncRNA regulation regarding individual cells, we focus on single-cell RNA-sequencing (scRNA-seq) da...

MicroRNA (miRNA) sponges influence the capability of miRNA-mediated gene silencing by competing for shared miRNA response elements and play significant roles in many physiological and pathological processes. It has been proved that computational or dry-lab approaches are useful to guide wet-lab experiments for uncovering miRNA sponge regulation. Ho...

In recent years, deep learning models (e.g. Convolutional Neural Networks (CNN) and Long Short-Term Memories (LSTM)), have been successfully applied to text sentiment analysis. However, the class-imbalance and unlabeled corpus still limit the accuracy of text sentiment classification. To overcome the two issues, in this work, we propose a new class...

Background Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology ha...

Inferring competing endogenous RNA (ceRNA) or microRNA (miRNA) sponge modules is a challenging and meaningful task for revealing ceRNA regulation mechanism at the module level. Modules in this context refer to groups of miRNA sponges which have mutual competitions and act as functional units for achieving biological processes. The recent developmen...

Purpose In this work, an algorithm named mRBioM was developed for the identification of potential mRNA biomarkers (PmBs) from complete transcriptomic RNA profiles of gastric adenocarcinoma (GA). Methods mRBioM initially extracts differentially expressed (DE) RNAs (mRNAs, miRNAs, and lncRNAs). Next, mRBioM calculates the total information amount of...

In molecular biology, microRNA (miRNA) sponges are RNA transcripts which compete with other RNA transcripts for binding with miRNAs. Research has shown that miRNA sponges have a fundamental impact on tissue development and disease progression. Generally, to achieve a specific biological function, miRNA sponges tend to form modules or communities in...

Autism Spectrum Disorder (ASD) is defined as polygenetic developmental and neurobiological disorders that cover a variety of development delays in social interactions. In recent years, computational methods using gene expression data have been proved to be effective in predicting ASD at the early stage. Feature selection methods directly affect the...

Background Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology ha...

Autism spectrum disorder (ASD) is a class of neurodevelopmental disorders characterized by genetic and environmental risk factors. The pathogenesis of ASD has a strong genetic basis, consisting of rare de novo or inherited variants among a variety of multiple molecules. Previous studies have shown that microRNAs (miRNAs) are involved in neurogenesi...

It is known that microRNAs (miRNAs) can inhibit message RNAs (mRNAs) translation, and thus directly influence the expression levels of them. On the other hand, the competing endogenous RNA (ceRNA) hypothesis indicates that different mRNAs compete with each other for binding with miRNAs, and further indirectly affect miRNA activity. Therefore, the m...

Until now, existing methods for identifying lncRNA related miRNA sponge modules mainly rely on lncRNA related miRNA sponge interaction networks, which may not provide a full picture of miRNA sponging activities in biological conditions. Hence there is a strong need of new computational methods to identify lncRNA related miRNA sponge modules. In thi...

After publication of this supplement article [1], it was brought to our attention that the Fig. 3 was incorrect. The correct Fig. 3 is as below.

Background: Studying multiple microRNAs (miRNAs) synergism in gene regulation could help to understand the regulatory mechanisms of complicated human diseases caused by miRNAs. Several existing methods have been presented to infer miRNA synergism. Most of the current methods assume that miRNAs with shared targets at the sequence level are working...

Until now, existing methods for identifying lncRNA related miRNA sponge modules mainly rely on lncRNA related miRNA sponge interaction networks, which may not provide a full picture of miRNA sponging activities in biological conditions. Hence there is a strong need of new computational methods to identify lncRNA related miRNA sponge modules. In thi...

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translate...

In the social security system, there still exist wilful insurance frauds. In this paper, to address the insufficient stability and randomness of the traditional insurance fraud evaluation model, we propose a new classifier called mixed ensemble model (MEM). Based on the principle of ensemble learning, MEM combines several different individual learn...

Background Studying multiple microRNAs (miRNAs) synergism in gene regulation could help to understand the regulatory mechanisms of complicated human diseases caused by miRNAs. Several existing methods have been presented to infer miRNA synergism. Most of the current methods assume that miRNAs with shared targets at the sequence level are working sy...

In the past decades, the ensemble systems have been shown as an efficient method to increase the accuracy and stability of classification algorithms. However, how to get a valid combination of multiple base-classifiers is still an open question to be solved. In this paper, based on the genetic algorithm, a new self-adaptive stacking ensemble model...

Background A microRNA (miRNA) sponge is an RNA molecule with multiple tandem miRNA response elements that can sequester miRNAs from their target mRNAs. Despite growing appreciation of the importance of miRNA sponges, our knowledge of their complex functions remains limited. Moreover, there is still a lack of miRNA sponge research tools that help re...

Background A microRNA (miRNA) sponge is an RNA molecule with multiple tandem miRNA response elements that can sequester miRNAs from their target mRNAs. Despite growing appreciation of the importance of miRNA sponges, our knowledge of their complex functions remains limited. Moreover, there is still a lack of miRNA sponge research tools that help re...

Background microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and they play an important role in various biological processes in the human body. Therefore, identifying their regulation mechanisms is essential for the diagnostics and therapeutics for a wide range of diseases. There have been a large number of researches wh...

The rate of 30-day hospital readmission is commonly used to measure the quality of medical service. To improve the hospital efficiency, in this study, we have proposed a balanced fuzzy C-Means LightGBM classifier (BFCMLGB) to predict the 30-day patient readmission using a published readmission dataset. The results show that the BFCM-LGB algorithm c...

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competiti...

Background miRBase is the primary repository for published miRNA sequence and annotation data, and serves as the “go-to” place for miRNA research. However, the definition and annotation of miRNAs have been changed significantly across different versions of miRBase. The changes cause inconsistency in miRNA related data between different databases an...

Background miRBase is the primary repository for published miRNA sequence and annotation data, and serves as the “go-to” place for miRNA research. However, the definition and annotation of miRNAs have been changed significantly across different versions of miRBase. The changes cause inconsistency in miRNA related data between different databases an...

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs with the length of ∼22 nucleotides. miRNAs are involved in many biological processes including cancers. Recent studies show that long non-coding RNAs (lncRNAs) are emerging as miRNA sponges, playing important roles in cancer physiology and development. Despite accumulating appreciation of th...

microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and they play an important role in various biological processes in the human body. Therefore, identifying their regulation mechanisms is essential for the diagnostics and therapeutics for a wide range of diseases. There have been a large number of researches which use gen...

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competiti...

It is known that noncoding RNAs (ncRNAs) cover ~98% of the transcriptome, but do not encode proteins. Among ncRNAs, long noncoding RNAs (lncRNAs) are a large and diverse class of RNA molecules, and are thought to be a gold mine of potential oncogenes, anti-oncogenes and new biomarkers. Although only a minority of lncRNAs is functionally characteriz...

microRNAs (miRNAs) are important gene regulators, controlling a wide range of biological processes and being involved in several types of cancers. Currently, several computational approaches have been developed to elucidate the miRNA-mRNA regulatory relationships. However, these approaches have their own limitations and we are still far from unders...

Background Recent studies have shown that the crosstalk between microRNA (miRNA) sponges plays an important role in human cancers. However, the co-regulation roles of miRNA sponges in protein-protein interactions (PPIs) are still unknown. Results In this study, we propose a multi-step method called miRSCoPPI to infer miRNA sponge co-regulation of...

Background MicroRNA (miRNA) sponges with multiple tandem miRNA binding sequences can sequester miRNAs from their endogenous target mRNAs. Therefore, miRNA sponge acting as a decoy is extremely important for long-term loss-of-function studies both in vivo and in silico. Recently, a growing number of in silico methods have been used as an effective t...

Recent findings show that coding genes are not the only targets that miRNAs interact with. In fact, there is a pool of different RNAs competing with each other to attract miRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The ceRNAs indirectly regulate each other via the titration mechanism, i.e. the increasing concentratio...

microRNAs (miRNAs) are important gene regulators at post-transcriptional level, and inferring miRNA-mRNA regulatory relationships is a crucial problem. Consequently, several computational methods of predicting miRNA targets have been proposed using expression data with or without sequence based miRNA target information. A typical procedure for appl...

Significant GO terms and KEGG pathways generated in Scenarios 4. (XLSX)

Understanding the synergism of multiple microRNAs (miRNAs) in gene regulation can provide important insights into the mechanisms of complex human diseases caused by miRNA regulation. Therefore, it is important to identify miRNA synergism and study miRNA characteristics in miRNA synergistic regulatory networks. A number of methods have been proposed...

Background: microRNAs (miRNAs) are short regulatory RNAs that are involved in several diseases, including cancers. Identifying miRNA functions is very important in understanding disease mechanisms and determining the efficacy of drugs. An increasing number of computational methods have been developed to explore miRNA functions by inferring the miR...

Discovering the regulatory relationships between microRNAs (miRNAs) and mRNAs is an important problem that interests many biologists and medical researchers. A number of computational methods have been proposed to infer miRNA-mRNA regulatory relationships, and are mostly based on the statistical associations between miRNAs and mRNAs discovered in o...

Motivation: MicroRNAs (miRNAs) play crucial roles in complex cellular networks by binding to the messenger RNAs (mRNAs) of protein coding genes. It has been found that miRNA regulation is often condition-specific. A number of computational approaches have been developed to identify miRNA activity specific to a condition of interest using gene expr...

microRNAs (miRNAs) are important gene regulators. They control a wide range of biological processes and are involved in several types of cancers. Thus, exploring miRNA functions is important for diagnostics and therapeutics. To date, there are few feasible experimental techniques for discovering miRNA regulatory mechanisms. Alternatively, predictio...

HBV (Hepatitis B Virus) infection is a severe global health problem. In recent years, mutations as an essential element in the HBV evolution have been extensively studied, however, the study of the conserved sequence for the evolution of HBV is still in its infancy. In this paper, we applied MEME (Multiple EM for Motif Elicitation) algorithm for mo...

HBV (Hepatitis B Virus) infection is a severe global health problem. In recent years, the single point mutation as an essential element in the HBV evolution has been extensively studied, however, only the limited mutation loci were reported. In this paper, we proposed a new method to apply MORE (Mining Optimal Risk PattErn sets) and RPSW (Risk and...