魏丽萍
研发及应用生物信息学方法来探索(1)转录及翻译中的反义调控机制,(2)非编码RNA的调控与被调控机制,(3)蛋白代谢网络的统计规律与进化。
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- 姓名:魏丽萍
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学术头衔:
博士生导师
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学科领域:
生物物理学
- 研究兴趣:研发及应用生物信息学方法来探索(1)转录及翻译中的反义调控机制,(2)非编码RNA的调控与被调控机制,(3)蛋白代谢网络的统计规律与进化。
魏丽萍博士是北京大学生物信息中心教授、主任、博士生导师,蛋白质工程与植物基因工程国家重点实验室副主任。之前曾任美国斯坦福大学医学系客座助理教授、Nexus Genomics公司共同创始人及首席科学家、美国Exelixis公司信息部研究员。获斯坦福大学医学信息学博士学位,布朗大学应用数学硕士学位,本科就读于中国科学技术大学无线电电子学系。魏丽萍博士是国际最大的生物信息学学会“International Society of Computational Biology (ISCB)”教育委员会及学术会议委员会的执行成员,国际SCI杂志Journal of Biomedical Informatics的副主编。目前的主要科研方向为研发及应用生物信息学方法来探索(1)转录及翻译中的反义调控机制,(2)非编码RNA的调控与被调控机制,(3)蛋白代谢网络的统计规律与进化。
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魏丽萍, Wuxue
Nucleic Acids Research, 2007, Vol. 35, Database issue D737-D741,-0001,():
-1年11月30日
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魏丽萍, Zhi-Qiang
BIOINFORMATICS ORIGINAL PAPER Vol. 23 no. 12 2007, pages 1444-1450,-0001,():
-1年11月30日
Motivation: The rapid accumulation of single amino acid polymorphisms (SAPs), also known as non-synonymous single nucleotide polymorphisms (nsSNPs), brings the opportunities and needs to understand and predict their disease association. Currently published attributes are limited, the detailed mechanisms governing the disease association of a SAP remain unclear and thus, further investigation of new attributes and improvement of the prediction are desired. Results: A SAP dataset was compiled from the Swiss-Prot variant pages. We extracted and demonstrated the effectiveness of several new biologically informative attributes including the structural neighbor profiles that describe the SAP's microenvironment, nearby functional sites that measure the structure-based and sequence-based distances between the SAP site and its nearby functional sites, aggregation properties that measure the likelihood of protein aggregation and disordered regions that consider whether the SAP is located in structurally disordered regions. The new attributes provided insights into the mechanisms of the disease association of SAPs. We built a support vector machines (SVMs) classifier employing a carefully selected set of new and previously published attributes. Through a strict protein-level 5-fold cross-validation, we attained an overall accuracy of 82.61%, and an MCC of 0.60. Moreover, a web server was developed to provide a user-friendly interface for biologists. Availability: The web server is available at http://sapred.cbi.pku.edu.cn/ Contact: sapred@mail.cbi.pku.edu.cn Supplementary information: Supplementary data are available at http://sapred.cbi.pku.edu.cn/supp.do
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魏丽萍, Yueyi
,-0001,():
-1年11月30日
Comparative genomics is a promising approach to the challenging problem of eukaryotic regulatory element identification, because functional noncoding sequences may be conserved across species from evolutionary constraints. We systematically analyzed known human and Saccharomyces cerevisiae regulatory elements and discovered that human regulatory elements are more conserved between human and mouse than are background sequences. Although S. cerevisiae regulatory elements do not appear to be more conserved by comparison of S. cerevisiae to Schizosaccharomyces pombe, they are more conserved when compared with multiple other yeast genomes (Saccharomyces paradoxus, Saccharomyces mikatae, and Saccharomyces bayanus). Based on these analyses, we developed a sequence-motif-finding algorithm called CompareProspector, which extends Gibbs sampling by biasing the search in regions conserved across species. Using human-mouse comparison, CompareProspector identified known motifs for transcription factors Mef2, Myf, Srf, and Sp1 from a set of human-muscle-specific genes. It also discovered the NFAT motif from genes up-regulated by CD28 stimulation in T-cells, which implies the direct involvement of NFAT in mediating the CD28 stimulatory signal. Using Caenorhabditis elegans-Caenorhabditis briggsae comparison, CompareProspector found the PHA-4 motif and the UNC-86 motif. CompareProspector outperformed many other computational motif-finding programs, demonstrating the power of comparative genomics-based biased sampling in eukaryotic regulatory element identification. [Supplemental data are available at www.genome.org and at http://compareprospector.stanford.edu. The program CompareProspector is available at http://compareprospector.stanford.edu.]
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魏丽萍, Xuwo
Nucleic Acids Research, 2006, Vol. 34, Web Server issue W551-W554,-0001,():
-1年11月30日
The recent availability of high-densityhumangenome tiling arrays enables biologists to conduct ChIP–chip experiments to locate the in vivo-binding sites of transcription factors in the human genome and explore the regulatory mechanisms. Once genomic regions enriched by transcription factor ChIP–chip are located, genome-scale downstream analyses are crucial but difficult for biologists without strong bioinformatics support. We designed and implemented the first web server to streamline the ChIP–chip downstream analyses. Given genome-scale ChIP regions, the cis-regulatory element annotation system (CEAS) retrieves repeat-masked genomic sequences, calculatesGCcontent, plots evolutionary conservation, maps nearby genes and identifies enriched transcription factor-binding motifs. Biologists can utilizeCEAS to retrieve useful information for ChIP–chip validation, assemble important knowledge to include in their publication and generate novel hypotheses (e.g. transcription factor cooperative partner) for further study. CEAS helps the adoption of ChIP–chip in mammalian systems and provides insights towards a more comprehensive understanding of transcriptional regulatory mechanisms. The URL of the server is http://ceas.cbi.pku.edu.cn.
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魏丽萍, Xizeng
BIOINFORMATICS ORIGINAL PAPER Vol. 21 no. 19 2005, pages3783-3793,-0001,():
-1年11月30日
Motivation: High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has certain limitations such as the lack of direct association with pathways. Results: We demonstrated the use of the KEGG Orthology (KO), part of theKEGGsuite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available standalone Python program that can contribute significantly to genome annotation and microarray analysis. Availability: Supplementary data and the KOBAS system are available at http://genome.cbi.pku.edu.cn/download.html Contact: weilp@mail.cbi.pku.edu.cn
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魏丽萍, Xin
Nucleic Acids Research, 2005, Vol. 33, Web Server issue W673-W676,-0001,():
-1年11月30日
Expressed
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魏丽萍, Yong
D156-D161 Nucleic Acids Research, 2007, Vol. 35, Database issue doi: 10. 1093 nar gkl782,-0001,():
-1年11月30日
Natural antisense transcripts (NATs) are reverse complementary at least in part to the sequences of other endogenous sense transcripts. Most NATs are transcribed from opposite strands of their sense partners. They regulate sense genes at multiple levels and are implicated in various diseases. Using an improved whole-genome computational pipeline, we identified abundant cis-encoded exonoverlapping sense–antisense (SA) gene pairs in human (7356), mouse (6806), fly (1554), and eight other eukaryotic species (total 6534). We developed NATsDB (Natural Antisense Transcripts DataBase, http://natsdb.cbi.pku.edu.cn/) to enable efficient browsing, searching and downloading of this currently most comprehensive collection of SA genes, grouped into six classes based on their overlapping patterns. NATsDB also includes non-exonoverlapping bidirectional (NOB) genes and nonbidirectional (NBD) genes. To facilitate the study of functions, regulations and possible pathological implications, NATsDB includes extensive information about gene structures, poly(A) signals and tails, phastCons conservation, homologues in other species, repeat elements, expressed sequence tag (EST) expression profiles and OMIM disease association. NATsDB supports interactive graphical display of the alignment of all supporting EST and mRNA transcripts of the SA and NOB genes to the genomic loci. It supports advanced search by species, gene name, sequence accession number, chromosome location, coding potential, OMIM association and sequence similarity.
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魏丽萍, Jianmin
W720-W724 Nucleic Acids Research, 2006, Vol. 34, Web Server issue doi: 10.1093 nar gkl167,-0001,():
-1年11月30日
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魏丽萍, Yong
Nucleic Acids Research, 2006, Vol. 34, No. 12 3465-3475,-0001,():
-1年11月30日
We developed a fast, integrative pipeline to identify cis natural antisense transcripts (cis-NATs) at genome scale. The pipeline mapped mRNAs and ESTs in UniGene to genome sequences in GoldenPath to find overlapping transcripts and combining information from coding sequence, poly(A) signal, poly(A) tail and splicing sites to deduce transcription orientation. We identified cis-NATs in 10 eukaryotic species, including 7830 candidate sense–antisense (SA) genes in 3915 SA pairs in human. The abundance of SA genes is remarkably low in worm and does not seem to be caused by the prevalence of operons. Hundreds of SA pairs are conserved across different species, even maintaining the same overlapping patterns. The convergent SA class is prevalent in fly, worm and sea squirt, but not in human or mouse as reported previously. The percentage of SA genes among imprinted genes in human and mouse is 24–47%, a range between the two previous reports. There is significant shortage of SA genes on Chromosome X in human and mouse but not in fly or worm, supporting X-inactivation in mammals as a possible cause. SA genes are over-represented in the catalytic activities and basic metabolism functions. All candidate cis-NATs can be downloaded from http://nats.cbi.pku.edu.cn/download/.
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魏丽萍, Zhaotao
,-0001,():
-1年11月30日
Background: Automated comparison of complete sets of genes encoded in two genomes can provide insight on the genetic basis of differences in biological traits between species. Gene ontology (GO) is used as a common vocabulary to annotate genes for comparison. Current approaches calculate the fold of unweighted or weighted differences between two species at the high-level GO functional categories. However, to ensure the reliability of the differences detected, it is important to evaluate their statistical significance. It is also useful to search for differences at all levels of GO. Results: We propose a statistical approach to find reliable differences between the complete sets of genes encoded in two genomes at all levels of GO. The genes are first assigned GO terms from BLAST searches against genes with known GO assignments, and for each GO term the abundance of genes in the two genomes is compared using a chi-squared test followed by false discovery rate (FDR) correction. We applied this method to find statistically significant differences between two cyanobacteria, Synechocystis sp. PCC6803 and Anabaena sp. PCC7120. We then studied how the set of identified differences vary when different BLAST cutoffs are used. We also studied how the results vary when only subsets of the genes were used in the comparison of human vs. mouse and that of Saccharomyces cerevisiae vs. Schizosaccharomyces pombe. Conclusion: There is a surprising lack of statistical approaches for comparing complete genomes at all levels of GO. With the rapid increase of the number of sequenced genomes, we hope that the approach we proposed and tested can make valuable contribution to comparative genomics.
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