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检索条件"任意字段=第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学"

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An integrated approach to identify the microRNAs regulation network modulating autophagy and cancer prognosis

An integrated approach to identify the microRNAs regulation ...

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Fengji Liang Xionghui Zhou Wcnyan Qiao Xingyi Hang Ling Yin Juan Liu Yinghui Li Shanguang Chen Jianghui Xiong Bioinformatics Group and Data Coordination Center State Key Lab of Space Medicine Fundamentals and Application(SMFA)China Astronaut Research and Training Center(ACC) School of Computer Science Wuhan University430072China National Scientific Data Sharing Platform for Population and Health Telemedicine Center Institute of Medical InformaticsGeneral Hospital of Chinese PLA

A core task of drug discovery study is to identify the dependency between the genetic/ molecular makeups of the human body and disease *** we proposed a novel method for systematically screening the microRNAs regulating cancer prognosis via driving a specific ppi(protein-protein interaction) *** this method,we integrated information from microRNAs expression,mRNAs expression and patient outcome,and tried to mine the in vivo dependency between microRNAs and ppi *** conditional dependency of the mRNAs expression(G),microRNAs expression(M) and phenotype(P) was calculated, and the permutation was conduct to screen the significant Conditional Mutual Information I (G,P|M).In this study we test the proposed method on autophagy protein networks in ovarian cancer as *** is a cellular process involved the degradation of cell's own components,in which cytoplasmic contents are sequestered into a double-membrane called autophagosome and then subsequently delivered to lysosome for *** identified a group of microRNAs,which could regulate the hub nodes of autophagy ppi *** experimentally demonstrated that the transfection of the mimics of these microRNAs could inhibit autophagy via inhibiting the target gene:***,the miRNA-target gene pair is significantly associated with prognosis in a cohort of ovarian cancer patients.

关键词： microRNAs An integrated approach to identify the microRNAs regulation network modulating autophagy and cancer prognosis

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Computational Prediction of RNA Tertiary Structure

Computational Prediction of RNA Tertiary Structure

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Yunjie Zhao Zhou Gong Changjun Chen Yi Xiao Biomolecular Physics and Modeling Group Department of PhysicsHuazhong University of Science and Technology

Building tertiary structures of non-coding RNA is required to understand their function and design new ***,the development of RNA tertiary structure building methods has provided some possible approaches to obtain lots of RNA 3D ***, current algorithms of RNA tertiary structure prediction give satisfactory accuracy only for small size and simple topology and many of them need manual ***,we present an automatic and fast program,3dRNA,for RNA tertiary structure prediction with reasonable accuracy for RNAs of larger size and complex *** focus on addressing two problems:1) automatic building of three-dimensional RNA structures and 2) ranking the predictions of the RNA tertiary structures or functional structural *** a benchmark test of about 300 RNA sequences with known experiment tertiary structures with length up to 101 nt,our method not only predicts hairpin and duplex structures with high prediction accuracy comparable to the best algorithm available at present,but also can give satisfactory prediction accuracy for RNA molecules with complex topology and large size,e.g.,structures with junctions and ***,our knowledge-based potential method program is able to rank the best models with the success rate of 98%and capture the structural features (***-canonical base pairs) with all-atom *** both two cases,our method performs consistently better than the existing methods.(AVAILABILITY:http://122.205.6.12 7/3dRNA/***)

关键词： RNA Computational Prediction of RNA Tertiary Structure

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Genetic Engineering of CymMV-resistant Phalaenopsis

Genetic Engineering of CymMV-resistant Phalaenopsis

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Shuguo Fan Department of Chemistry and Life Science Chuxiong Normal University Institute for Bio-resources Development and Utilization in Central Yunnan Plateau

Background:The orchid has been one of the most economic floricultural crops in China. Among them,Phalaenopsis *** first place in commercial value in the orchid industry. However,viral infections result in the great reduction in both quality and quantity of flowers, hence becoming a limiting factor in the orchid *** mosaic virus(CymMV) is one of the most prevalent plant viruses in *** aim of this research is to generate CymMV-resistant Phalaenopsis amabilis overexpressing either the sense or anti-sense strand of the CymMV coat protein(CP) genes using particle ***,the transgenic orchids will be resistant against viral infection. Methods:Calli have been induced from *** regeneration system has been established from *** gene comprising the capsid proteins of CymMV has been constructed,optimum conditions for particle bombardment have been *** calli and transgenic plantlets have been screened on selection *** selection medium was optimized for shoot induction with L-methionine sulfoximine(MSO) added as selection *** was done in both solid and liquid medium. Results:It was found that liquid media and experiment showed that selection in liquid medium was faster and more *** amplification of the inserted CP genes were used for genotyping,and PCR Southern assay confirm the insertion of anti-sense strand of CymMV CP genes into several lines of *** *** blot and Western blot have also been done for the putative transformed plants,and viral inoculation and detection will be performed on the transgenic Phalaenopsis when they grow to be big. Conclusions:Our results showed that the transgenic *** has been successfully created,and hopefully,the transgenic orchids will be resistant against viral infection.

关键词： Cymbididum mosaic virus(CymMV) Phalaenopsis amabilis coat protein(CP)

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Innovative Technologies for Protein Structure Predictions

Innovative Technologies for Protein Structure Predictions

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Tonghua Li Jiangming Sun Dapeng Li Peisheng Cong Shengnan Tang Department of Chemistry Tongji University

Background:Prediction of protein secondary and tertiary structures from its sequence is long-standing challenge in computational *** there are many intelligent algorithms have been developed,however,there is steel a space of promotion accuracy for predicting protein secondary and tertiary ***,we introduce SPSSMPred and BSalign constructed by our group recently in this field and several innovation technologies were proposed to break through the bottleneck of prediction of protein structure. Protein secondary structure prediction:We propose for the first time a structural position-specific scoring matrix(SPSSM),and establish an unprecedented database of 9 million sequences and their *** database,when combined with a purpose- designed BLAST tool,provides a novel prediction tool:*** the SPSSMPred was validated on a large dataset(10 814 entries),the Q3 accuracy of the protein secondary structure prediction was 93.4%.Our approach was tested on the two latest EVA sets;accuracies of 82.7 and 82.0%were achieved,far higher than can be achieved using other *** further evaluation,we tested our approach on newly determined sequences(141 entries),and obtained an accuracy of 89.6%.For a set of low-homology proteins(40 entries), the SPSSMPred still achieved a Q3 value of 84.6%. Protein tertiary structure prediction:Identification of protein structural neighbors to a query is fundamental in structure and function *** present BS-align,a systematic method to retrieve backbone string neighbors from primary sequences as templates for protein *** backbone conformation of a protein is represented by the backbone string, which is confirmed benefits for prediction of turns in *** backbone string of a query can be accurately predicted by two innovative technologies:a knowledge-driven sequence alignment and encoding of a backbone string element *** used an algorithm to extract local combinational variable

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Predicting recombination hotspots in yeast based on DNA sequence and chromatin structure

Predicting recombination hotspots in yeast based on DNA sequ...

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Bingjie Zhang Guoqing Liu School of Mathematics Physics and Biological EngineeringInner Mongolia University of Science and Technology The Institute of Bioengineering and Technology Inner Mongolia University of Science and Technology

Background:Meiotic recombination does not occur evenly across the genome,but instead occurs at relatively high frequencies in some genomic regions(hotspots) and relatively low frequencies in others(coldspots).Recombination depends not only on sequence features, but also on chromatin *** and characterization of hotspots and coldspots are considerably significant for that information about hotspots/coldspots would shed light on the mechanism of recombination and genome *** of high-resolution recombination rates using genetic experiments is time-consuming and ***,it is necessary to develop computational methods to predict recombination rates or recombination hotspots in the *** far,there is no model for predicting recombination hotspots in which chromatin structure is *** this study,we analyzed the correlation between recombination and nucleosome occupancy,and presented a model for predicting recombination hotspots based on the sequence and nucleosome occupancy in yeast. Methods:The relationship between recombination and nucleosome occupancy is estimated by Pearson correlation.A model based on IDQD(increment of diversity combined with quadratic discriminant) algorithm using tetranucleotide frequencies in sequences and nucleosome occupancy as features is developed to predict recombination hotspots/coldspots in yeast. Results:Our results show that the regions with high nucleosome occupancy have high recombination rate in the yeast *** correlation between genome-wide recombination rate and nucleosome occupancy is significant(R-0.151,P<0.001).The prediction accuracy of hotspots based on sequence alone is 80%.The prediction accuracy increased to 81.6%when nucleosome occupancy is used as an additional feature. Conclusion:Our data show that recombination is significantly positively correlated with nucleosome occupancy in the yeast genome,and hotspots prediction accuracy is improved when nucleosom

关键词： Recombination hotspots Nucleosome IDQD

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Classification of Reactions Catalyzed by Oxidoreductases and Hydrolases Using Computational Methods

Classification of Reactions Catalyzed by Oxidoreductases and...

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Aixia Yan Xiaoying Hu State Key Laboratory of Chemical Resource Engineering Department of Pharmaceutical EngineeringP.O.Box 53Beijing University of Chemical Technology

The Enzyme Commission(EC) classification system is widely used in chemistry and biology and is maintained by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology(NC-IUBMB).Enzymes are classified into six main classes;each main class is reclassified into several subclasses;a subclass is classified into *** this EC system,each enzyme has its unique EC number:EC a.b.c.d,where "a" refers to the six main classes of enzymes;"b" indicates the subclasses;"c" represents the subsubclasses;"d" is the serial number of the enzyme in its *** method of enzyme classification is based on several criteria,such as reaction types,substrates,transferred groups,and acceptor groups. In this work,several computational models for classification of reactions catalyzed by hydrolases and oxidoreductases were developed using three different computational methods. The overall breaking and making of bonds of reactions were *** physicochemical properties for the reacting bond in the substrate of each enzymatic reaction were calculated to describe the characteristics of each *** 311 reactions catalyzed by hydrolases (EC 3.b.c.d) and the 651 reactions catalyzed by oxidoreductases(EC l.b.c.d) were classified by Kohonen's Self-Organizing Map(SOM),by a support vector machine(SVM),and by hierarchical clustering analysis(HCA).For the 311 reactions catalyzed by hydrolases,the classification accuracy of 95.8%by a SOM and 97.7%by an SVM was *** the 651 reactions catalyzed by oxidoreductases,the classification accuracy was 93.4%and 96.3%by a SOM and a SVM,*** similarities of reactions reflected by the physicochemical effects of reacting bonds were compared with the traditional Enzyme Commission(EC) classification system.

关键词： Hydrolases Oxidoreductase Reaction classification Kohonen's Self-Organizing Map(SOM) support vector machine(SVM)

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Integrating epigenetic and transcriptome data to identify consensus gene modules and signatures of paclitaxel responsiveness across multiple cancer types

Integrating epigenetic and transcriptome data to identify co...

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Xu Li Fengji Liang Xingyi Hang Ling Yin Yinghui Li Shanguang Chen 熊江辉 Bioinformatics Group and Data Coordination Center State Key Lab of Space Medicine Fundamentals and Application(SMFA)China Astronaut Research and Training Center(ACC)

Background:Paclitaxel(Taxol) is a widely used anti-cancer chemotherapeutic drug for many cancer ***,multiple studies focused on identifying cancer-specific paclitaxel responsive regulatory elements and signatures in particular type of *** we integrated DNA Methylation and gene expression profiling data to test whether there are shared gene modules and signatures across multiple types of cancer. Methods and Results:The promoter CGI methylation and mRNA expression profiles of multiple types of cancer were integrated to identify the epigenetically regulated genes, by selecting genes which show significant negative correlation between its expression level and promoter CGI *** Cox multivariate regression analysis was adopted to screen genes which are significantly associated with survival times of Paclitaxel treated *** overlap signature genes across multiple types of cancers were investigated in human protein-protein interaction *** demonstrated that these shared gene modules enriched in gene networks related to cell adhesion,tight junction pathways,synthesis of methionine adenosyltransferase,cell cycle progression and ***,by combining above features and constructing an SVM classifier,we demonstrated that the consensus gene modules could be used to classify the patient outcomes in various types of cancer. Conclusions:We demonstrated that epigenetically regulated genes and pathways is a common feature related to clinical outcome of paclitaxel treatment in multiple types of cancer.

关键词： Paclitaxel DNA methylation Regression analysis SVM

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GeSICA:Genome Segmentation from Intra-Chromosomal Associations

GeSICA:Genome Segmentation from Intra-Chromosomal Associatio...

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Lin Liu Yiqian Zhang Jianxing Feng Ning Zheng Junfeng Yin Yong Zhang Department of Bioinformatics School of Life Science and TechnologyTongji University Department of Mathematics Tongji University

Background:Various aspects of genome organization have been explored based on data from distinct technologies,including histone modification ChIP-Seq,3C,and its derivatives. Recently developed Hi-C techniques enable the genome-wide mapping of DNA interactomes, thereby providing the opportunity to study genome organization in detail,but these methods also pose challenges in methodology development. Methods:We propose a two-step strategy in this *** the first step we categorize the entire human genome into two different *** the second step we further segregated the regions with some state into more detailed clusters by employing a Markov Clustering algorithm Results:We developed Genome Segmentation from Intra-Chromosomal Associations, or GeSICA,to explore genome organization and applied the method to Hi-C data in human GM06990 and K562 *** calculates a simple logged ratio to efficiently segment the human genome into regions with two distinct states that correspond to rich and poor functional element *** the rich regions,Markov Clustering was subsequently applied to segregate the regions into more detailed *** binding sites of the insulator, cohesion,and transcription complexes are enriched in the boundaries between neighboring clusters,indicating that inferred clusters may have fine organizational features. Conclusions:Our study presents a novel analysis method,known as GeSICA,which gives insight into genome organization based on Hi-C *** is open-source and freely available at:http://***/～zhanglab/GeSICA/.

关键词： Hi-C genome organization Markov Clustering

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Construction and identification of a recombinant lentiviral expression vector containing hTERT gene

Construction and identification of a recombinant lentiviral ...

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者： Shuying Gao Central Laboratory of Peking University Shenzhen Hospital Shenzhen PKU-HKUST Medical Center

Objective:To construct a recombinant lentiviral vector containing human telomerase reverse transcriptase(hTERT) gene,and investigate its expression in HeLa cells. Methods:Using gateway reaction,hTERT gene from the cloning vector pENTR221- hTERT was recombined into the lentiviral expression vector pLenti6.3/V5-DEST to construct a recombinant lentiviral vector pLenti6.3/***,the recombinant lentiviral vector was cotransfected with packaging plasmids pLP1,pLP2 and pLP/VSVG into 293FT cells to produce recombinant *** resulting recombinant lentivirus were used to transduce HeLa *** cell clones were selected using blasticidin,the chromosomal integration of exogenous hTERT gene were detected by PCR,and the effect of recombinant lentivirus transduction on hTERT gene mRNA expression in HeLa cells were analysed by RT-PCR. Results:It was confirmed that the recombinant lentiviral vector pLenti6.3/V5-hTERT carried hTERT gene and the hTERT gene was packaged into *** the recombinant lentivirus were transduced into HeLa cells,blasticidin-resistant colonies obtained,their chromosomal DNA integrated exogenous hTERT gene,and the expression level of hTERT mRNA was higher than control HeLa cells without lentivirus transduction. Conclusion:The recombinant lentivirus vector pLenti6.3/V5-hTERT has been successfully constructed,which can increase the hTERT gene mRNA expression in HeLa cells.

关键词： human telomerase reverse transcriptase(hTERT) gene recombinant lentivirus cotransfection

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Proteomics Data-Driven Theoretical Biology Research

Proteomics Data-Driven Theoretical Biology Research

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第五届全国生物信息学与系统生物学学术大会暨国际生物信息学前沿研讨会高通量时代的生物信息学与系统生物学

作者：贺福初 State Key Laboratory of Proteomics Beijing Proteome Research CenterBeijing Institute of Radiation Medicine

The proteomics is an especial fountain of finding global biological *** datasets could provide a rich ground for the discovery of the fundamental *** is the central player in most cellular processes,and its distribution,abundance and interaction are regulated *** have explored multiple proteomes from these aspects,and discovered some intrinsic regular patterns. We explore the general trends for the selective expression of proteins,and its evolutionary meaning about the selective utilization of the structural factors contributing to biological complexity[1].We found that multidomain proteins or only older domain-containing containing proteins are significantly overrepresented in certain-state proteomes(CSPs,i.e., all the proteins expressed at certain physiological states) compared with the full genome-encoded proteome(GEP),which is a trend that is stronger in multicellular organisms than in unicellular *** comparing across CSPs,we found that multidomain proteins are more overrepresented in complex tissues than in simpler ***,biological complexity under certain conditions is more significantly realized by diverse domain organization than by the emergence of new types of domain. The principle that determines the abundance of different proteins in a proteome is of fundamental significance for an understanding of the building blocks of the *** found three regular patterns in the proteome-wide distribution of protein abundance across species[2]:protein abundance is positively correlated with the protein's origination time or sequence conservation during evolution;it is negatively correlated with the protein's domain number and positively correlated with domain coverage in protein structure,and the correlations became more significant during the course of evolution;protein abundance can be further stratified by the function of the protein,whereby proteins that act on material conversion and transportation(mass c

关键词： Proteomics Data-Driven Theoretical Biology Research

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