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Towards efficiency in rare disease research： what is distinctive and important？

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Science China(life Sciences) 2017年第7期60卷 686-691页

作者： Jinmeng Jia Tieliu Shi The center for bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biology the Institute of Biomedical Sciences and School of Life Sciences East China Normal University Shanghai 200241 China

Characterized by their low prevalence, rare diseases are often chronically debilitating or life threatening. Despite their low prevalence, the aggregate number of individuals suffering from a rare disease is estimated to be nearly 400 million *** the past decades, efforts from researchers, clinicians, and pharmaceutical industries have been focused on both the diagnosis and therapy of rare diseases. However, because of the lack of data and medical records for individual rare diseases and the high cost of orphan drug development, only limited progress has been achieved. In recent years, the rapid development of next-generation sequencing(NGS)-based technologies, as well as the popularity of precision medicine has facilitated a better understanding of rare diseases and their molecular etiology. As a result, molecular subclassification can be identified within each disease more clearly, significantly improving diagnostic accuracy. However, providing appropriate care for patients with rare diseases is still an enormous challenge. In this review, we provide a brief introduction to the challenges of rare disease research and make suggestions on where and how our efforts should be focused.

关键词： rare disease rare disease diagnosis and treatment data standard data sharing orphan drugs

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

The secondary periodic element ■ and its applications

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Science China Mathematics 2025年第1期 207-222页

作者： Jianguo Hong Xiangjun Wang Yu Zhang Science College Shijiazhuang University School of Mathematical Sciences Nankai University center for applied Mathematics Tianjin University

Let p≥7 be a *** prove that ■ survives to E∞in the Adams-Novikov spectral ***,using the Thom map Φ:■,we can see that h0h3also survives to E∞in the classical Adams spectral *** an application of these results,we ...

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The genetic program Of oocytes can be modified in vivo in the zebrafish ovary

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Journal of Molecular Cell Biology 2018年第6期10卷 479-493页

作者： Xiaotong Wu Weimin Shen Bingjie Zhang Anming Meng Laboratory of Molecular Developmental Biology State Key Laboratory of Membrane BiologyTsinghua-Peking Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China center for Stem Cell Biology and Regenerative Medicine MOE Key Laboratory of BioinformaticsTsinghua-Peking Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China

Oocytes,the irreplaceable gametes for generating a new organism,are matured in the ovary of living female *** is unknown whether any genetic manipulations can be applied to immature oocytes inside the living *** a proof-of-concept, we here demonstrate genetic amendments of zebrafish immature oocytes within the *** microinjection in situ (OMIS) stimulates tissue repair responses,but some of the microinjected immature oocytes are matured,ovulated and *** OMIS-mediated Cas9 approach,ntla and gata5 loci of oocytes arrested at prophase I of meiosis are successfully edited before *** OMIS,high efficiency of biaUeUc mutations in single or multiple loci using Cas9/gRNAs allows immediate manifestation of mutant phenotypes in Fo embryos and multiple transgenes can co-express the reporters in Fo embryos with patterns similar to germline transgenic ***,maternal knockdown of dnmt1 by antisense morphoino via OMIS results in a dramatic decrease of global DNA methylation level at the dome stage and causes embryonic lethalityprior to segmentation ***,OMIS opens a door to efficiently modify the genome and provides a possibility to re repair genetically abnormal oocytes in situ.

关键词： oocytes microinjection gene editing transgenesis morpholino zebrafish

Architectural proteins for the formation and maintenance of the 3D genome

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Science China(life Sciences) 2020年第6期63卷 795-810页

作者： Mengfan Li Jingbo Gan Yuao Sun Zihan Xu Junsheng Yang Yujie Sun Cheng Li Peking-Tsinghua center for life Sciences Academy for Advanced Interdisciplinary Studies School of Life Sciences Peking UniversityBeijing 100871China State Key Laboratory of Membrane Biology School of Life Sciences Biomedical Pioneering Innovation Center (BIOPIC) Peking UniversityBeijing 100871China center for Statistical Science Center for Bioinformatics School of Life Sciences Peking UniversityBejjing 100871China

Eukaryotic genomes are densely packaged into hierarchical three-dimensional(3D) structures that contain information about gene regulation and many other biological processes. With the development of imaging and sequencing-based technologies, 3D genome studies have revealed that the high-order chromatin structure is composed of hierarchical levels, including chromosome territories, A/B compartments, topologically associated domains, and chromatin loops. However, how this chromatin architecture is formed and maintained is not completely clear. In this review, we introduce experimental methods to investigate the 3D genome, review major architectural proteins that regulate 3D chromatin organization in mammalian cells, such as CTCF(CCCTC-binding factor), cohesin, lamins, and transcription factors, and discuss relevant mechanisms such as phase separation.

关键词： 3D genome architectural protein Hi-C

Structured Learning in Biological Domain

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Journal of Systems Science and Systems Engineering 2020年第4期29卷 440-453页

作者： Canh Hao Nguyen bioinformatics center Instute for Chemical ResearchKyoto UniversityUjiKyotoJapan

Biological domain has been blessed with more and more data from biotechnologies as well as data integration *** the renaissance of machine learning and artificial intelligence,there is so much promise of data-driven biological knowledge ***,it is not straight forward due to the complexity of the domain knowledge hidden in the *** any level,be it atoms,molecules,cells or organisms,there are rich interdependencies among biological *** learning approaches in this domain usually involves analyzing interdependency structures encoded in graphs and related *** this report,we review our work in developing new Machine Learning methods for these applications with improved performances in comparison with state-of-the-art *** show how the networks among biological components can be used to predict properties.

关键词： Structured learning sparse modeling systems biology deep learning

Microbial Dark Matter: from Discovery to Applications

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Genomics, Proteomics & bioinformatics 2022年第5期20卷 867-881页

作者： Yuguo Zha Hui Chong Pengshuo Yang Kang Ning MOE Key Laboratory of Molecular Biophysics Hubei Key Laboratory of Bioinformatics and Molecular-imagingCenter of Artificial Intelligence BiologyDepartment of Bioinformatics and Systems BiologyCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

With the rapid increase of the microbiome samples and sequencing data,more and more knowledge about microbial communities has been ***,there is still much more to learn about microbial communities,including billions of novel species and genes,as well as countless spatiotemporal dynamic patterns within the microbial communities,which together form the microbial dark *** this work,we summarized the dark matter in microbiome research and reviewed current data mining methods,especially artificial intelligence(AI)methods,for different types of knowledge discovery from microbial dark *** also provided case studies on using AI methods for microbiome data mining and knowledge *** summary,we view microbial dark matter not as a problem to be solved but as an opportunity for AI methods to explore,with the goal of advancing our understanding of microbial communities,as well as developing better solutions to global concerns about human health and the environment.

关键词： Microbiome Dark matter Artificial intelligence Knowledge discovery Application

Silencing of Transposable Elements by piRNAs in Drosophila:An Evolutionary Perspective

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Genomics, Proteomics & bioinformatics 2017年第3期15卷 164-176页

作者： Shiqi Luo Jian Lu State Key Laboratory of Protein and Plant Gene Research Center for BioinformaticsCollege of Life Sciences and Peking-Tsinghua Center for Life SciencesPeking University Beijing Advanced Innovation center for Food Nutrition and Human Health College of Food Science and Nutritional EngineeringChina Agricultural University

Transposable elements （TEs） are DNA sequences that can move within the genome. TEs have greatly shaped the genomes, transcriptomes, and proteomes of the host organisms through a variety of mechanisms. However, TEs generally disrupt genes and destabilize the host genomes, which substantially reduce fitness of the host organisms. Understanding the genomic distribution and evolutionary dynamics of TEs will greatly deepen our understanding of the TE-mediated bio- logical processes. Most TE insertions are highly polymorphic in Drosophila melanogaster, providing us a good system to investigate the evolution of TEs at the population level. Decades of theoretical and experimental studies have well established ＂transposition-selection＂ population genetics model, which assumes that the equilibrium between TE replication and purifying selection determines the copy number of TEs in the genome. In the last decade, P-element-induced wimpy testis （PIW1）- interacting RNAs （piRNAs） were demonstrated to be master repressors of TE activities in Droso- phila, The discovery of piRNAs revolutionized our understanding of TE repression, because it reveals that the host organisms have evolved an adaptive mechanism to defend against TE invasion. Tremendous progress has been made to understand the molecular mechanisms by which piRNAs repress active TEs, although many details in this process remain to be further explored. The inter- action between piRNAs and TEs well explains the molecular mechanisms underlying hybrid dysge- nesis for the IoR and P-M systems in Drosophila, which have puzzled evolutionary biologists for decades. The piRNA repression pathway provides us an unparalleled system to study the co-evolutionary process between parasites and host organisms.

关键词： Transposable element piRNA Hybrid dysgenesis Evolution Drosophila

GOAL: the comprehensive gene ontology analysis layer

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Science China(Information Sciences) 2016年第7期59卷 86-93页

作者： Jong Cheol JEONG George LI Xue-Wen CHEN Department of Pathology Harvard Medical School Beth Israel Deaconess Medical Center bioinformatics and Computational life Sciences Laboratory University of Kansas Department of Computer Science Wayne State University

Homogeneity or heterogeneity of cells is the most fundamental and important features of analyzing biological associations of genes and gene products. Recent bioinformatics technology requires an automated high-throughput analysis application that can handle massively produced data from next generation sequences and dramatically increased size of public proteomic/genomic databases. Although Gene ontology(GO) database has been newly spotlighted on its wide coverage of machine-readable terminologies, its complex DB schema and vast amount of applications utilizing GO without deep considerations of GO term relations dilute the actual power of GO-based analysis and resulted in misleading/under estimated outcomes. Meanwhile, our recent studies showed that BSM score, a new way of measuring functional similarity, clearly outperformed existing conventional methods. However, implementing BSM score that requires integrating multiple databases and calculating scoring matrix is not trivial and even difficult for bioinformatics experts; therefore, a web-based graphical user interface(GUI) tool, Gene Ontology Analysis Layer(GOAL: http://***/chenlab/goal) is introduced to provide user-friendly GO application powered by state of art functional similarity metric,BSM score.

关键词： gene ontology molecular function functional similarity network-based analysis BSM score