主要方向：整合分析全基因组ChIP-chip/Seq、核小体定位、组蛋白修饰数据、开发生物信息学算法
主要成果：开发Model-based analysis of ChIP-Seq (MACS)、Cistrome数据库
Homepage: Liu Lab
注：已离开学术界，任职于GV20 Oncotherapy，董事会主席）
Bradley E. Bernstein
主要方向：Epigenomic Regulation in Development and Cancer
主要成果：The NIH Roadmap Epigenomics Mapping Consortium
Homepage: https://bernstein.dfci.harvard.edu/
Nancy Kleckner
主要方向：The Physical Biology of Chromosomes
主要成果：3C（Capturing Chromosome Conformation，通讯）
Homepage: Nancy Kleckner
University of Massachusetts Medical School
主要方向：genomic tools to the study of proteins of the epigenome: histones, transcription factors, nucleosome remodelers, and RNA polymerase II (RNAPII)
主要成果：ChEC-seq；DNase-seq；CUT&Tag；CUT&Run；CUT&Tag2for1；MulTI-Tag
Homepage: https://research.fredhutch.org/henikoff/en.html
University of California San Diego
任兵
主要方向：非编码序列如何指导基因表达的时空模式，表观遗传机制如何在发育过程中调节这些序列的作用
主要成果：chip-chip；识别和表征增强子的转录控制元件；Paired-seq；Paired-tag
Homepage: Bing Ren, Ph.D.
Massachusetts Institute of Technology(MIT)
Manolis Kellis
主要方向：epigenetic modifications to define chromatin states；comparative genomics；annotation of the non-coding genome；Regulatory Networks
主要成果：参与构建ENCODE数据库；ChromHMM: automating chromatin-state discovery and characterization
Homepage: Manolis Kellis (Kamvysselis)
Stanford University
主要方向: investigating how the dysfunction of heterochromatin, repetitive elements and transposons contributes to the oncogenic and aging processes
主要成果: Transcriptionally active HERV-H retrotransposons demarcate topologically associating domains in human pluripotent stem cells(Nature Genetics, 2019)
Homepage: https://zhangyxlab.github.io/
张垲（ 导师：任兵)
主要方向：embracing a multidisciplinary approach to address pressing challenges in Regulatory Genomics
主要成果：A single-cell atlas of chromatin accessibility in the human genome(Cell, 2021)
Homepage: https://lab.kaizhang.org/
Northwestern University
主要方向：interested in cancer genomics and has demonstrated how epigenome and 3D genome structure are altered and led to gene dysregulation in different types of tumor
主要成果： A comparative encyclopedia of DNA elements in the mouse genome(Nature, 2014)
Homepage: http://yuelab.org/index.html
Washington University
Ting Wang
主要方向：investigating the evolutionary model of mobile elements (or transposable elements) and their roles in basic biology and cancer, including their genetic and epigenetic regulation
主要成果：Exploring genomic data coupled with 3D chromatin structures using the WashU Epigenome Browser(Nature Methods, 2022)
Homepage: https://wang.wustl.edu/about/
二：基因组学
Broad Institute of MIT and Harvard
Eric S. Lander(谨慎，有负面报道)
主要方向：human genetic variation; human population history; genome evolution; regulatory elements; long non-coding RNAs; three-dimensional folding of the human genome; and genome-wide screens to discover the genes essential for biological processes using CRISPR-based genome editing
主要成果：Broad Institute创始人、人类基因组计划首席科学家、GATK、IGV
Homepage: Eric S. Lander
Genentech
Aviv Regev
主要方向：single-cell genomics；The evolution of gene regulation；networks that regulate genes, define cells and tissues, and influence health and disease
主要成果：Fungal orthogroups；Cancer module map；Module networks；international Human Cell Atlas project首席科学家
Homepage: https://www.broadinstitute.org/regev-lab
Dana-Farber and Harvard Medical School
李恒
主要方向：比对等算法开发
主要成果：SAM格式设计；SAMtools；bwa；Minimap2；Chromap
Homepage: Heng Li's Homepage
Massachusetts Institute of Technology
Bonnie Berger
主要方向：Computational molecular biology；Network Inference；PPI networks；protein structural motif recognition and discovery；Compressive Genomics；molecular self-assembly and mis-assembly, and functional genomics
主要成果：Global alignment of multiple protein interaction networks with application to functional orthology detection
Homepage: Bonnie Berger | MIT Mathematics
Children's Hospital of Philadelphia
王凯
主要方向：bioinformatics methods to advance genomic medicine, deep neural network for long-read sequencing, deep phenotyping on electronic health records, graduate rotation and undergraduate research projects
主要成果：ANNOVAR, wANNOVAR, PennCNV
Homepage: Wang Lab
北京大学
主要方向：机器学习与生物和医学大数据分析、人类细胞图谱与人体系统数字孪生、单细胞生物信息学分析
主要成果：
Homepage: 张学工-清华大学自动化系
Cornell University
Edward Buckler
主要方向：Plant Breeding and Genetics Section; Quantitative and statistical genetics in maize, cassava, biofuel grasses, and grapes
主要成果：TASSEL: software for association mapping of complex traits in diverse samples(Bioinformatics 2007)
Homepage: https://www.maizegenetics.net/
中山大学
主要方向：开发检测一系列常见和罕见嵌合突变的方法; 探索人类不同发育阶段突变谱的特征和之间的潜在关联; 对嵌合突变进行泛癌检测和分析
主要成果：Accurate detection of mosaic variants in sequencing data without matched controls. (Nat Biotechnol, 2020)
Homepage: https://sls.westlake.edu.cn/Our_Faculty/202104/t20210407_9156.shtml
The University of Texas
Nicholas Navin
主要方向：Single Cell Genomics; Cancer Evolution；development of single cell genome sequencing technologie；study cancer as an evolutionary process in which clones undergo selection and expansion in response to selective pressures
主要成果：Tumour evolution inferred by single-cell sequencing（Nature 2011）
Homepage: https://faculty.mdanderson.org/profiles/nicholas_navin.html
Momiao Xiong
主要方向：Methods for Genome-wide Association Studies，Methods for Functional Genomics Sequencing Studies
主要成果：Genome-wide efficient mixed-model analysis for association studies
Homepage：http://www.xzlab.org/index.html
University of Chicago
龙漫远
主要方向：Evolution of gene essentiality in development；Evolutionary analysis of gene interactions with new genes
主要成果：
Homepage: | Ecology & Evolution
University College London
杨子恒
主要方向：develop statistical models and computer software for population genetic and phylogenetic
主要成果：BP&P: Bayesian analysis of genomic sequence data under the multispecies coalescent model；Phylogenetic analysis by maximum likelihood （PAML）
Homepage: http://abacus.gene.ucl.ac.uk/
复旦大学
主要方向: 发展和运用群体遗传学方法和计算生物学手段，致力于研究人群遗传结构、环境适应和微观进化等方面的科学问题
主要成果:
Homepage: http://pog.fudan.edu.cn/#/home
Carnegie Mellon University
马坚
主要方向：机器学习算法的开发；人类基因组结构和功能与疾病的联系；智能医疗和智能健康；多模态数据整合
主要成果：Infinite Sites Model、InferCARs、Nucleome Browser
Homepage: Carnegie Mellon School of Computer Science
中国农业科学院农业基因组研究所
阮珏
主要方向：基因组组装算法、极低频点突变检测、基因组结构变异检测
主要成果：Pseudo-sanger、wtdbg2、SMARTdenovo
Homepage: 中国农科院基因组所
St. Jude Children's Research Hospital
Jinghui Zhang
主要方向：the development of highly accurate and sensitive computational methods for analyzing large-scale genomic data, especially in the area of detecting and analyzing genetic variations and somatic mutations
主要成果：参与人类基因组计划；开发BLAST（co-author）；CREST maps somatic structural variation in cancer genomes with base-pair resolution（Nature Methods 2011）；Copy Number Segmentation by Regression Tree in Next Generation Sequencing（Nature Methods 2015）
Homepage: https://www.stjuderesearch.org/site/lab/zhang
上海交通大学
主要方向: 1)high throughput phenotyping by using hyperspectral images and remote sensing images from satellites and drones; 2) the development of innovative statistical methods and computing tools for gene mapping and genomic selection
主要成果: Mixed linear model approach adapted for genome-wide association studies(Nature Genetics, 2010)
Homepage: https://zzlab.net/
中国农业科学院农业基因组研究所
黄三文
主要方向：利用组学大数据开拓植物生物学前沿并推动作物育种变革；发起了“优薯计划”，旨在利用基因组设计育种变革马铃薯的育种和繁殖方式
主要成果：Haplotype-resolved genome analyses of a heterozygous diploid potato. (Nature Genetics, 2020)
Homepage: https://agis.caas.cn/rcpy/gjjrc/gjgccrctszcjh/230423.htm
中科院遗传发育研究所
主要方向：统计遗传学与基因组育种，致力于全基因组关联分析（GWAS）和基因组选择/预测（GS/GP）算法的研究
主要成果：Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-wide Association Studies.(PLoS Genetics, 2016)
Homepage: https://faculty.hzau.edu.cn/liuxiaolei/zh_CN/index.htm
哈尔滨工业大学
王亚东
主要方向: 基因组数据分析算法开发
主要成果: Long-read-based human genomic structural variation detection with cuteSV(Genome Biology, 2020)
Homepage: http://homepage.hit.edu.cn/wangyadong
三：RNA组学
中国科学院大学生物物理所
陈润生（中国生信第一人）
主要方向：胚胎早期发育以及干细胞重编程过程中长非编码RNA以及编码小肽的系统发现和功能机制研究
主要成果：参加人类基因组1%和水稻基因组工作草图的研究；非编码RNA数据库NONCODE；数据库NPInter（非编码RNA与其它生物大分子相互作用）
Homepage: 陈润生-中国科学院大学-UCAS
Stanford University
王永雄 Wing Hung Wong
主要方向：贝叶斯统计、计算生物学；基因调控网络
主要成果：采样算法并应用到贝叶斯推理的方法；开发了微阵列基因芯片表达数据和RNA测序数据分析的创新模型和方法
Homepage: Welcome to the Wong Lab
北京大学
主要方向：动植物中编码和非编码RNA的转录后调控研究 、癌症等疾病中新型RNA分子标识物的发现和机理研究、 机器学习等数据挖掘技术的研究及其在基因组学大数据上的应用
主要成果：
Homepage: 鲁 志-清华大学生命学院
张强锋（导师：张元豪 Howard Y. Chang）
主要方向：使用高通量深度测序的手段来探测RNA二级结构和计算建模，RNA功能模体（motif）等有效预测或发现方法，蛋白-蛋白、RNA-RNA、以及蛋白-RNA相互作用网络
主要成果：VRmol: an Integrative Web-Based Virtual Reality System to Explore Macromolecular Structure （Bioinformatics 2020)；RISE: a database of RNA interactome from sequencing experiments（Nucleic Acids Res 2018)
Homepage: 张强锋实验室
University of California San Diego
Gene Yeo
主要方向：manipulating RNA processing in development and disease using induced pluripotent stem cell and murine models； RNA genomics technology and therapeutics development
主要成果：seCLIP
Homepage: Institute for Genomic Medicine
中科院上海营养与健康研究所
杨力
主要方向：构建高效计算生物学新体系，揭示外显子环形RNA在生成加工和功能作用水平的多层次调控新机制；开展大数据整合及计算生物学分析，主要发现RNA单碱基编辑和修饰互作的分子基础，并进一步利用核酸编辑酶构建高效基因组碱基编辑新体系
主要成果：Circular intronic long noncoding RNAs（Molecular cell 2015）；Complementary sequence-mediated exon circularization（2014 Cell）
Homepage: 杨力----中国科学院上海营养与健康研究所
The University of Texas MD Anderson Cancer Center
Han Liang（导师：Wen-Hsiung Li）
主要方向：bioinformatics tool development, integrated cancer genomic analysis, RNA regulation/modification, and cancer systems biology
主要成果：Whole-exome sequencing combined with functional genomics reveals novel candidate driver cancer genes in endometrial cancer；TANRIC: an interactive open platform to explore the function of lncRNAs in cancer
Homepage: https://faculty.mdanderson.org/profiles/liang_han.html
浙江大学
郭国骥
主要方向：单细胞RNA组学
主要成果：Construction of a human cell landscape at single-cell level（Cell 2020）;
Mapping the Mouse Cell Atlas by Microwell-Seq(Cell 2018)
Homepage: 郭国骥-浙江大学个人主页
Johns Hopkins University
Steven Salzberg
主要方向: develop software for aligning and assembling genomes representing a wide range of species, transcriptome analysis, and microbiome analysis
主要成果: Bowtie2, TopHat2, Cufflinks, HISAT, StringTie and FLASH
Homepage: https://salzberg-lab.org/
UCLA
Jingyi Jessica Li
主要方向：developing statistical and computational methods，including association measures, high-dimensional variable selection, and classification metrics， scRNA-seq
主要成果：An accurate and robust imputation method scImpute for single-cell RNA-seq data Clipper: p-value-free FDR control on high-throughput data from two conditions
Homepage：http://jsb.ucla.edu/
四：蛋白质组学
Eidgenössische Technische Hochschule Zürich
Ruedi Aebersold
主要方向：One of the pioneers in the field of proteomics, Mass Spectrometry, Systems Biology, Bioinformatics,
主要成果：ICAT & SRM & SWATH
Homepage: Ruedi Aebersold
Max-Planck-Institute of Biochemistry
Matthias Mann
主要方向：Mass Spectrometry, Systems Biology, Bioinformatics, Signal Transduction, Posttranslational modifications, Metabolic diseases, Clinical proteomics, Cancer
主要成果：SILAC & MaxQuant
Homepage: Mann lab
Scripps Research Institute
主要方向：开发前沿蛋白质组学技术，用于高通量地从最少量的临床样本精确定量最多的蛋白质，推动定量蛋白质组学的研究；生物标记的鉴定
主要成果：Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps（2015）；Multi-organ proteomic landscape of COVID-19 autopsies（2020）
Homepage: Guomics Laboratory
暨南大学
主要方向：neuroscience and artificial intelligence
主要成果：AlphaFold（通讯）
Homepage: About
John Jumper
主要方向：protein structure prediction
主要成果：AlphaFold（一作）
Homepage: Science Team
The University of Washington
David Baker
主要方向：Deep learning for protein structure refinement and protein design; Designing molecular switches, enzymes, and motors; Designing delivery vehicles for targeted intracellular delivery of biologics
主要成果：Protein Structure Prediction Using Rosetta(Methods in enzymology 2004)
Homepage: https://www.bakerlab.org/
Tel Aviv University
Nir Ben-Tal
主要方向：computational structural biology， including both methods development and applications to selected problems
主要成果：ConSurf、Rate4Site
Homepage: https://en-lifesci.tau.ac.il/profile/bental
Max Planck Institute for Developmental Biology
主要方向：protein function and structure prediction；sequence search and assembly in metagenomics
主要成果：The HHpred interactive server for protein homology detection and structure prediction；
HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
Homepage: https://www.mpibpc.mpg.de/soeding
University of Texas Southwestern Medical Center
Nick Grishin
主要方向：develop new computational approachesto explore protein sequence-structure
主要成果：PROMALS3D: a tool for multiple protein sequence and structure alignments；AL2CO: calculation of positional conservation in a protein sequence alignment；ECOD；ProSMoS；
Homepage: Grishin Lab: Home Page
University of Michigan Medical School
Yang Zhang
主要方向：develop bioinformatics approaches to predict the three-dimensional structures of proteins from amino acid sequences ；Assemble Protein Structures from Cryo-EM
主要成果：I-TASSER（通讯）: a unified platform for automated protein structure and function prediction；TM-align: a protein structure alignment algorithm based on the TM-score；CR-I-TASSER: Assemble Protein Structures from Cryo-EM Density Maps using Deep Convolutional Neural Networks
Homepage: Yang Zhang, Ph.D. | Computational Medicine and Bioinformatics | Michigan Medicine
Memorial Sloan Kettering Cancer Center
Dana Pe'er
主要方向：combines single cell technologies, genomic datasets and machine learning algorithms to address fundamental questions in biomedical science
主要成果：Using Bayesian networks to analyze expression data（Journal of computational biology 2000）
Homepage: https://www.mskcc.org/research/ski/labs/dana-pe-er
山东大学
杨建益
主要方向：Protein structure and function prediction；Protein structure alignment；Protein-ligand binding site prediciton
主要成果：I-TASSER（一作）
Homepage: Yang Lab
King Abdullah University of Science and Technology
高欣
主要方向：1) developing theory and methodology in the fields of machine learning and algorithms; and 2) solving key open problems in biological and medical fields through building computational models, developing machine-learning techniques, and designing effective and efficient algorithms
主要成果：DEEPre: sequence-based enzyme EC number prediction by deep learning(Bioinformatics 2018)
Homepage: https://sfb.kaust.edu.sa/Pages/Home.aspx
Chinese University of Hong Kong
李煜（导师：高欣）
主要方向：working at the intersection between machine learning, healthcare and bioinformatics, developing new machine learning methods to resolve the computational problems in biology and healthcare, especially the structured learning problems
主要成果：DEEPre: sequence-based enzyme EC number prediction by deep learning(Bioinformatics 2018)
Homepage: https://liyu95.com/
西湖大学
The Center for Brains, Minds and Machines (CBMM) of MIT
Tomaso Poggio
主要方向：Brain Imaging；Cellular & Molecular Neuroscience；Cognitive Neuroscience；ComputationalNeuroscience
主要成果：Networks for approximation and learning；Face recognition: Features versus templates；
Hierarchical models of object recognition in cortex
Homepage: https://cbmm.mit.edu/about/people/poggio
复旦大学
赵兴明
主要方向：开发新的计算方法用于分子网络的构建和分析；脑核磁共振图像的处理；脑功能神经网络的构建和处理；疾病相关分子通路的识别；药物靶蛋白预测和药物重定位
主要成果：PhosD: inferring kinase–substrate interactions based on protein domains (Bioinformatics 2017)；Prediction of drug combinations by integrating molecular and pharmacological data（PLoS computational biology 2011）
Homepage: http://comp-sysbio.org/
New York University
主要方向：Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival；Pathways Understanding；Study of Protein-Protein Interactions Using Probabilistic Graphical Models；Computer vision；Bayesian Network；Robotics
主要成果：Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network；Continuous Time Bayesian Networks；Multi-Class Segmentation with Relative Location Prior
Homepage: Daphne Koller's Research Group
Weizmann Institute of Science
Nir Freidman
主要方向：combine advanced experimental and mathematical approaches to study intercellular communication；T cell activation and differentiation；Characterizing T cell receptor repertoires using high throughput sequencing (TCR-seq)
主要成果：Gaussian Process Networks
Homepage: https://www.weizmann.ac.il/immunology/NirFriedman/
北京大学
韩敬东
主要方向：开发数据整合和网络分析的计算方法；衰老的系统生物学研究
主要成果：Evidence for dynamically organized modularity in the yeast protein–protein interaction network；Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq
Homepage: 韩敬东-北京大学前沿交叉学科研究院
The Chinese University of Hong Kong
Kevin Y Yip
主要方向：computational biology and bioinformatics (CBB)；Whole-genome identification of sequence elements；Computational modeling of gene regulation
主要成果：参与ENCODE；Harp: A practical projected clustering algorithm
Homepage: Home of Kevin Yip
University of Pennsylvania
Nancy Ruonan Zhang
主要方向：Statistics, Computer Science, and Biology, seeking new ways to think about and work with genomic data
主要成果：参与ENCODE；Graph-based change-point detection；A modified Bayes information criterion with applications to the analysis of comparative genomic hybridization data；SAVER: gene expression recovery for single-cell RNA sequencing
Homepage: Department of Statistics and Data Science
Kai Tan
主要方向：using genomics and systems biology approaches to understand the gene regulatory factors underlying cellular processes
主要成果：Global view of enhancer–promoter interactome in human cells；A comparative genomics approach to prediction of new members of regulons
Homepage: https://www.med.upenn.edu/apps/faculty/index.php/g275/p8885111
Mingyao Li
主要方向：statistical genetics and genomics；use statistical and machine learning approaches to understand cellular heterogeneity ；characterize gene expression diversity across cell types；to study the patterns of cell state transition and crosstalk of various cells using data generated from single-cell transcriptomics studies
主要成果：MetaDiff；PennSeq
Homepage: https://www.med.upenn.edu/apps/faculty/index.php/g275/p8122973
UT Southwestern Medical Center
Jian Zhou
主要方向：Decoding Genomic Sequence；Evolution of Regulatory Genome；Data Science and AI Methods
主要成果：Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk；Predicting effects of noncoding variants with deep learning–based sequence model
Homepage: Jian Zhou - Home
Johns Hopkins University
Jean Fan
主要方向：develop methods for analyzing single-cell spatially resolved transcriptomic sequencing and imaging data；cellular heterogeneity on cancer pathogenesis and prognosis
主要成果：VeloViz: RNA-velocity informed embeddings for visualizing cellular trajectories；Characterizing transcriptional heterogeneity through pathway and gene set overdispersion analysis；Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists
Homepage: Jean Fan - Johns Hopkins Biomedical Engineering
University of Michigan
Lana Garmire
主要方向：Integrative omics/clinic data analysis；Develop computational methods to analyze high-throughput data from next-generation sequencing
主要成果：Cox-nnet: an artificial neural network method for prognosis prediction of high-throughput omics data；Deep learning–based multi-omics integration robustly predicts survival in liver cancer；
Homepage: Lana Garmire, Ph.D. | Computational Medicine and Bioinformatics | Michigan Medicine
Univeristy of Hong Kong
Yuanhua Huang
主要方向：developing statistical machine learning methods and computational algorithms for analysing biomedical data, particularly single-cell genomic data
主要成果：BRIE: transcriptome-wide splicing quantification in single cells；Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference
Homepage: Huang Lab @ HKU Home
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