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Highly Regional Genes:graph-based gene selection for single-cell RNA-seq data

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Journal of Genetics and Genomics 2022年第9期49卷 891-899页

作者： Yanhong Wu Qifan Hu Shicheng Wang Changyi Liu Yiran Shan Wenbo Guo Rui Jiang Xiaowo Wang Jin Gu MOE Key Laboratory of bioinformatics BNRIST Bioinformatics DivisionDepartment of AutomationTsinghua UniversityBeijing 100084China

Gene selection is an indispensable step for analyzing noisy and high-dimensional single-cell RNA-seq(scRNA-seq)*** with the commonly used variance-based methods,by mimicking the human maker selection in the 2D visualization of cells,a new feature selection method called HRG(Highly Regional Genes)is proposed to find the informative genes,which show regional expression patterns in the cell-cell similarity *** mathematically find the optimal expression patterns that can maximize the proposed scoring *** comparison with several unsupervised methods,HRG shows high accuracy and robustness,and can increase the performance of downstream cell clustering and gene correlation ***,it is applicable for selecting informative genes of sequencing-based spatial transcriptomic data.

关键词： Single-cell RNA-sequencing Feature selection Spatially resolved transcriptomic data Regional patterns Graphical models

VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder

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Genomics, Proteomics & bioinformatics 2018年第5期16卷 320-331页

作者： Dongfang Wang Jin Gu MOE Key Laboratory of bioinformatics BNRIST Bioinformatics Division & Center for Synthetic and Systems BiologyDepartment of Automation Tsinghua University

Single-cell RNA sequencing(scRNA-seq) is a powerful technique to analyze the transcriptomic heterogeneities at the single cell level. It is an important step for studying cell subpopulations and lineages, with an effective low-dimensional representation and visualization of the original scRNA-Seq data. At the single cell level, the transcriptional fluctuations are much larger than the average of a cell population, and the low amount of RNA transcripts will increase the rate of technical dropout events. Therefore, scRNA-seq data are much noisier than traditional bulk RNA-seq data. In this study, we proposed the deep variational autoencoder for scRNA-seq data(VASC), a deep multi-layer generative model, for the unsupervised dimension reduction and visualization of scRNA-seq data. VASC can explicitly model the dropout events and find the nonlinear hierarchical feature representations of the original data. Tested on over 20 datasets, VASC shows superior performances in most cases and exhibits broader dataset compatibility compared to four state-of-the-art dimension reduction and visualization methods. In addition, VASC provides better representations for very rare cell populations in the 2D visualization. As a case study, VASC successfully re-establishes the cell dynamics in pre-implantation embryos and identifies several candidate marker genes associated with early embryo development. Moreover, VASC also performs well on a 10× Genomics dataset with more cells and higher dropout rate.

关键词： Single cell RNA sequencing Deep variational autoencoder Dimension reduction Visualization Dropout

Antioxidant activity and free radical scavenging activities of Streptomyces *** MJM 10778

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Asian Pacific Journal of Tropical Medicine 2014年第12期7卷 962-967页

作者： Dong-Ryung Lee Sung-Kwon Lee Bong-Keun Choi Jinhua Cheng Young-Sil Lee Seung Hwan Yang Joo-Won Suh division of bioscience and bioinformatics Myongji UniversityYoungin-siGyeonggi-do 449728Korea Center for Neutraceutical and Pharmaceutical Materials Myongji UniversityYongin-siGyeonggi-do 449728Korea

Objective:To investigate the antioxidant activity of soil-borne ***:The total phenolic contents,the level of antioxidant potential by DPPH radical scavenging activity,MO scavenging activity,and ABTS radical scavenging activity in ethyl acelale extract were ***:The 16 S rDNA sequencing analysis revealed that Streptomyces *** MJM *** was isolated from Hambak ***,has 99.9% similarity to Streptomyces misionensis(***) NBRC *** physiological and the morphological test revealed that the strain MJM 10778 has different characteristics from the strain *** entire antioxidant assay with the ethyl acelale extract displayed good radical scavenging *** IC_(50) values of the strain MJM 10778 extract on DPPH,.*** ABTS radicals were identified to he 92.8 μg/mL,0.02 μg/ml,and 134.9 μg/mL,*** ethyl acetate extract of the strain MJM 10778 showed an 81.500% of cell viability at 100 μg/mL in Raw264.7cell viability ***:The results obtained suggesl that the ethyl acetate extract of Streptomyces *** MJM 10778 could be considered as a potential source of drug for the diseases that is caused by free radicals with its anti-oxidant activities and low cytotoxicity.

关键词： Streptomyces sp.strain MJM 10778 Antioxidant activity DPPH radical scavenging assay NO radical scavenging assay

TCM network pharmacology:A new trend towards combining computational,experimental and clinical approaches

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Chinese Journal of Natural Medicines 2021年第1期19卷 1-11页

作者： WANG Xin WANG Zi-Yi ZHENG Jia-Hui LI Shao Institute for TCM-X MOE Key Laboratory of Bioinformatics/Bioinformatics DivisionBNRISTDepartment of AutomationTsinghua UniversityBeijing 100084China

Traditional Chinese medicine(TCM)is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of *** holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and *** gave birth to a new method featuring holistic and systematic"network target",a core theory and method of network *** is also an important research object of network *** network pharmacology,which aims to understand the network-based biological basis of complex diseases,TCM syndromes and herb treatments,plays a critical role in the origin and development process of network *** review introduces new progresses of TCM network pharmacology in recent years,including predicting herb targets,understanding biological foundation of diseases and syndromes,network regulation mechanisms of herbal formulae,and identifying disease and syndrome biomarkers based on biological *** studies show a trend of combining computational,experimental and clinical approaches,which is a promising direction of TCM network pharmacology research in the *** that TCM network pharmacology is still a young research field,it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.

关键词： Network pharmacology Traditional Chinese medicine Network target Computation Experiment Clinical approach

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

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Cancer Biology & Medicine 2024年第4期21卷 312-330页

作者： Qian Zhang Mingran Yang Peng Zhang Bowen Wu Xiaosen Wei Shao Li Institute for TCM-X MOE Key Laboratory of BioinformaticsBioinformatics DivisionBNRISTDepartment of AutomationTsinghua UniversityBeijing 100084China

Gastric cancer(GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development;therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

关键词： Gastric cancer inflammation-induced tumorigenesis multi-omics artificial intelligence network-based methods

Challenges in Understanding Genome-Wide DNA Methylation

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Journal of Computer Science & Technology 2010年第1期25卷 26-34页

作者：张伟奇 Andrew D. Smith Cold Spring Harbor Laboratory Cold Spring Harbor bioinformatics division TNLIST and MOE Key Lab of Bioinformatics Tsinghua University Department of Biological Sciences University of Southern California

DNA methylation is a chemical modification of the bases in genomes. This modification, most frequently found at CpG dinucleotides in eukaryotes, has been identified as having multiple critical functions in broad and diverse species of animals and plants, while mysteriously appears to be lacking from several other well-studied species. DNA methylation has well known and important roles in genome stability and defense, its pattern change highly correlates with gene regulation. Much evidence has linked abnormal DNA methylation to human diseases. Most prominently, aberrant DNA methylation is a common feature of cancer genomes. Elucidating the precise functions of DNA methylation therefore has great biomedical significance. Here we provide an update on large-scale experimental technologies for detecting DNA methylation on a genomic scale. We also discuss new prospect and challenges that computational biologist will face when analyzing DNA methylation data.

关键词： DNA methylation epigenome computational epigenomics

Complicated evolutionary patterns of microRNAs in vertebrates

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Science China(Life Sciences) 2008年第6期51卷 552-559页

作者： WANG XiaoWo, ZHANG XueGong & LI YanDa MOE Key Laboratory of bioinformatics and bioinformatics division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China 1. MOE Key Laboratory of bioinformatics and bioinformatics division TNLIST / Department of Automation Tsinghua University Beijing 100084 China

MicroRNAs (miRNAs) are a class of ～22 nt long endogenous non-coding RNAs that play important regulatory roles in diverse organisms. Up to now, little is known about the evolutionary properties of these crucial regulators. Most miRNAs were thought to be phylogenetically conserved, but recently, a number of poorly-conserved miRNAs have been reported and miRNA innovation is shown to be an ongoing process. In this work, through the characterization of an miRNA super family, we studied the evolutionary patterns of miRNAs in vertebrates. Recently generated miRNAs seem to evolve rapidly during a certain period following their emergence. Multiple lineage-specific expansions were observed. Homolgous premiRNAs may produce mature products from the opposite stem arms following tandem duplications, which may have important contribution to miRNA innovation. Our observations of miRNAs' complicated evolutionary patterns support the notion that these key regulatory molecules may play very active roles in evolution.

关键词： microRNA evolution miRNA:miRNA* interconversion lineage specific duplication

Improving cis-regulatory elements modeling by consensus scaffolded mixture models

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Science China(Information Sciences) 2013年第1期56卷 219-229页

作者： JIANG HongShan ZHAO Ying CHEN WenGuang ZHANG XueGong Department of Computer Science and Technology Tsinghua University MOE Key Laboratory of bioinformatics and the bioinformatics division Department of AutomationTsinghua University

A position weight matrix(PWM) is widely accepted as a probabilistic representation for modeling protein-DNA binding *** studies showed that for factors which bind to divergent binding sites,mixtures of multiple PWMs improve *** propose a consensus scaffolded mixutre PWM(CSM) model to improve cis-regulatory elements modeling by allowing overlapping components represented by a set of PWMs,each of which corresponds to a binding pattern and is scaffolded by a degenerate *** addition,we propose a learning algorithm that involves an initial structure learning stage based on the frequent pattern mining and a refining stage based on the expectation maximization(EM) *** assess the merits of CSM using three independent *** a case-study of transcription factor Leu3,the derived CSM models agree with conventional mixtures but show better fitness according to Fermi-Dirac *** of the human-mouse conservation of predicted binding sites of 83 JASPAR transcription factors(TFs) shows that the CSM is as good as or better than the simple mixture,the context-specific independent(CSI) mixture,and the single PWM model,for 83%,84%,and 75% of the cases,***-fold cross validation on 46 TRANSFAC datasets shows that CSM model has better generality than other mixture models.

关键词： position weight matrix cis-regulatory elements mixture models frequent pattern mining EM algorithm

Comprehensive simulation of metagenomic sequencing data with non-uniform sampling distribution

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Frontiers of Electrical and Electronic Engineering in China 2018年第2期6卷 175-185页

作者： Shansong Liu Kui Hua Sijie Chen Xuegong Zhang MOE Key Lab of bioinformatics Bioinformatics Division TNLIST and Department of Automation Tsinghua University Beijing 100084 China

Background： Metagenomic sequencing is a complex sampling procedure from unknown mixtures of many genomes. Having metagenome data with known genome compositions is essential for both benchmarking bioinformatics software and for investigating influences of various factors on the data. Compared to data from real microbiome samples or from defined microbial mock community, simulated data with proper computational models are better for the purpose as they provide more flexibility for controlling multiple factors. Methods： We developed a non-uniform metagenomic sequencing simulation system （nuMetaSim） that is capable of mimicking various factors in real metagenomic sequencing to reflect multiple properties of real data with customizable parameter settings. Results： We generated 9 comprehensive metagenomic datasets with different composition complexity from of 203 bacterial genomes and 2 archaeal genomes related with human intestine system. Conclusion： The data can serve as benchmarks for comparing performance of different methods at different situations, and the software package allows users to generate simulation data that can better reflect the specific properties in their scenarios.

关键词： simulation metagenomic sequencing data non-uniform sampling nuMetaSim