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第五届全国生物信息学与系统生物学学术大会

作者： Xionghui Zhou Fengji Liang 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) Beijing China Bioinformatics Group and Data Coordination Center State Key Lab of Space Medicine Fundamentals and Application (SMFA) China Astronaut Research and Training Center (ACC) Beijing China School of Computer Science Wuhan University Wuhan China School of Computer Science Wuhan University Wuhan China

Background: The bone is the most frequent target of metastatic breast ***, the underlying molecular mechanisms are *** many microarray studies have reported gene signatures that can predict metastasis in breast cancer, predicting cancer metastasis to a specific organ, such as to bone, remains a challenge in cancer ***: Previously we proposed a concept CoMi (Context Specific miRNA activity), which could quantify the regulation activity of miRNA on specific context (CoMi activity) by calculating the statistical difference of the expression level between the miRNAtargets and non-targets in a given context (GO term biological process), and demonstrated its application on predicting *** we extend this concept to CoMi module and use it to predict whether the cancer will metastasize to ***, CoMi features which are significant associated with the bone metastasis are identified by Cox proportional hazards *** on the significant CoMi features, miRNAs regulate on the same context are regarded as a significant miRNA regulation *** each significant CoMi module is used to predict bone metastasis of breast cancer patients by sum up all the risk scores (Cox proportional hazards regression) of CoMi features in the ***: We tested the proposed method on a breast cancer cohort contain 855 samples' gene expression profiles together with bone metastasis *** bone metastasis specific CoMi modules are identified, such as module 'hemopoiesis', which has a log rank p value of 9.05e-07 in train dataset, 0.0075 in test dataset and 0.0031 in independent test *** the hematopoietic stem cell niche is a potential therapeutic target for bone metastatic tumors, our results might facilitate to identify the miRNAs regulation modules involved in hematopoietic stem cell ***: We proposed the concept of CoMi activity module, and identified some CoMi activity modules which

关键词： Context specific miRNA activity metastasis organ prediction miRNA regulation network

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In silico cancer drug screening based on microRNAs regulationnetworks

In silico cancer drug screening based on microRNAs regulatio...

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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： Lida Zhu Fengji Liang Juan Liu Yinghui Li Jianghui Xiong Computer School Wuhan University Bioinformatics Group and Data Coordination Center State Key Lab of Space Medicine Fundamentals and Application(SMFA)China Astronaut Research and Training Center(ACC) Computer School Wuhan UniversityChina

Background:Severalstudies,such as the Connectivity Map(CMAP),showed that gene expression profiles could reflect drug perturbationeffects,and can be used in drug screening and drug *** we introduced a concept CoMi(Context-Specific miRNA Activity),and provide a novel perspective on drug mechanisms of *** this work,we intend to construct a virtual drug screening system and test whether CoMi could be used to capture the common features of approved cancer drugs and discriminate them from other candidate chemicals. Methods & Results:(l)We used correlation analysisby integrating the drugsensitive data(GI50) with gene expression datafrom diverse cancer cell lines in NCI60 datasets,and generated the drug sensitivity gene *** calculating the overlap rate between the drug sensitivity gene sets with disregulated gene set in breast cancer,we defined a drug-disease association index andgenerated a pool of 445 breast cancer associated compounds,including 61 positive drugs(approved breast cancer drugs) and 384 negative drugs.(2)Using the most significant differential CoMi features in positive *** drugs,a NaiveBayesian classifier could accurately predict the successful breast cancer drugs(AUC 0.86),and its performance was significantly exceed the mRNA signature based drug screening system (AUC 0.75),far superior to naive CMAP screening system(AUC0.56).(3)Further analysis of the network consisted of CoMi with good classification performance,highlighted some high connected miRNA nodes,including important cancer-related miRNAs(mir-495) and tumor suppressormiRNA(mir-520d);In addition,a number of high connectivity functional gene setsare also closely related with the biological processes of cancer(for example,cell differentiation).(4)Integrating differential expressed CoMi induced by Paclitaxel with breast cancer specific CoMi,weexaminedits application on classifying drug responsiveness in a breast cancer cohort using paclitaxel as neoadjuvant thera

关键词： microRNAs In silico cancer drug screening based on microRNAs regulationnetworks

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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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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

作者： Fengji Liang Xionghui Zhou Wenyan Qiao Xingyi Hang Ling Yin Juan Liu Yinghui Li Shanguang Chen Jianghui Xiong Telemedicine Center Institute of Medical Informatics General Hospital of Chinese PLA Beijing China School of Computer Science Wuhan University 430072 China Bioinformatics Group and Data Coordination Center State Key Lab of Space Medicine Fundamentals and Application (SMFA) China Astronaut Research and Training Center (ACC) Beijing China School of Computer Science Wuhan University 430072 China Bioinformatics Group and Data Coordination Center State Key Lab of Space Medicine Fundamentals and Application (SMFA) China Astronaut Research and Training Center (ACC) Beijing China National Scientific Data Sharing Platform for Population and Health Beijing China

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 .

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Proceedings of Reanimation 2017, the French Intensive Care Society International Congress Abstracts

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ANNALS OF INTENSIVE CARE 2017年第1期7卷 7-7页

作者： [Anonymous] Réanimation polyvalente Faculté de médecine de Sfax Sfax Tunisia Réanimation polyvalente CHU Habib Bourguiba Sfax Tunisia ICU CHU Habib Bourguiba Sfax Tunisia Anesthesia and Intensive Care Charles Nicolle Teaching Hospital Tunis Tunisia Intensive care Charles Nicolle Hospital Tunis Tunisia Anesthésie réanimation CHU Ibn Rochd Casa Casablanca Morocco Reanimation des urgences chirurgicale Chu Ibn Rochd Casablanca Morocco Service de réanimation des urgences chirurgicales CHU IBN ROCHD de Casablanca Casablanca Morocco Service d’accueil des urgences Chu Ibn Rochd Casablanca Morocco Pôle de réanimation hôpital salengro C.H.R.U. - Lille Avenue Oscar Lambret Lille France Centre de biologie pathologie génétique Centre Hospitalier Régional Universitaire de Lille Lille France Inserm cic 1435/urgences/samu Centre Hospitalier Universitaire de Limoges Limoges France Services urgences adultes/samu-smur/inserm cic1435 C.H.U de Limoges Limoges France Service de réanimation polyvalente Centre Hospitalier Universitaire de Limoges Limoges France Inserm cic 1435/réanimation polyvalente C.H.U de Limoges Limoges France Urgences/samu Centre Hospitalier Universitaire de Limoges Limoges France Service urgences adultes/samu-smur C.H.U de Limoges Limoges France Service de maladies infectieuses Centre Hospitalier Universitaire de Limoges Limoges France Bactériologie-virologie-hygiène/umr-s 1092 Centre Hospitalier Universitaire de Limoges Limoges France Medical icu Hospital Abderrahmen Mami De Pneumo-Phtisiologie Ariana Tunisia Réanimation médicale Hôpital Abderrahmen Mami Ariana Tunisia Department of intensive care and toxicology Centre d’Assistance Médicale Urgente Tunis Tunisia Service de réanimation médicale Centre d’assistance médicale-urgente Tunis Tunisia Reanimation Centre Hôspitalier Henri Duffaut Avignon France Interne en anesthésie réanimation C.H. Régional Universitaire de Lille (CHRU de Lille) Lille France Réanimation polyvalente Hospital Center De Dunk

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[Correlations between clusters of protein-DNA binding sites and the binding experimental data allow to predict a structure of regulatory modules].

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Biofizika 2012年第2期57卷 212-214页

作者： Nikulova, A.A. Polishchuk, M.S. Tumanian, V.G. Makeev, V.I. Mironov, A.A. Favorov, A.V. Department of Bioengineering and Bioinformatics Moscow State University Moscow Russia Institute of Problems of Data Transmission Russian Academy of Sciences Moscow Russia Engelhardt Institute of Molecular Biology Russian Academy of Sciences Moscow Russia University of California Berkeley Berkeley USA Vavilov Institute of General Genetics Russian Academy of Sciences Moscow Russia State Research Institute for Genetics and Selection of Industrial Microorganisms «GosNIIgenetika» Moscow Russia The Sidney Kimmel Cancer Center at Johns Hopkins University Baltimore Baltimore USA

Here we analyzed an option to predict the structure of cis-regulatory modules that consist of binding sites of different proteins (heterogeneous cis-regulatory modules) using mutual positional correlations between protein-DNA binding experimental data and computationally identified clusters of binding sites for each of the proteins.

关键词： binding site cluster ChIP-chip ChIP-Seq cis-regulatory module CORE-CLUST CRM GenometriCorr PatternClust

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Predicting bone metastasis of breast cancer using context-specific miRNA regulation modules

Predicting bone metastasis of breast cancer using context-sp...

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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： Xionghui Zhou Fengji Liang Juan Liu Yinghui Li Shanguang Chen Jianghui Xiong School of Computer Science Wuhan University 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 University.WuhanChina

Background:The bone is the most frequent target of metastatic breast ***, the underlying molecular mechanisms are *** many microarray studies have reported gene signatures that can predict metastasis in breast cancer,predicting cancer metastasis to a specific organ,such as to bone,remains a challenge in cancer study. Methods:Previously we proposed a concept CoMi(Context Specific miRNA activity), which could quantify the regulation activity of miRNA on specific context(CoMi activity) by calculating the statistical difference of the expression level between the miRNA targets and non-targets in a given context(GO term biological process),and demonstrated its application on predicting *** we extend this concept to CoMi module and use it to predict whether the cancer will metastasize to ***,CoMi features which are significant associated with the bone metastasis are identified by Cox proportional hazards regression. Based on the significant CoMi features,miRNAs regulate on the same context are regarded as a significant miRNA regulation *** each significant CoMi module is used to predict bone metastasis of breast cancer patients by sum up all the risk scores(Cox proportional hazards regression) of CoMi features in the module. Results:We tested the proposed method on a breast cancer cohort contain 855 samples' gene expression profiles together with bone metastasis *** bone metastasis specific CoMi modules are identified,such as module 'hemopoiesis',which has a log rank p value of 9.05e-07 in train dataset,0.0075 in test dataset and 0.0031 in independent test dataset. Considering the hematopoietic stem cell niche is a potential therapeutic target for bone metastatic tumors,our results might facilitate to identify the miRNAs regulation modules involved in hematopoietic stem cell niche. Conclusions:We proposed the concept of CoMi activity module,and identified some CoMi activity modules which could predict bone metas

关键词： Context specific miRNA activity metastasis organ prediction miRNA regulation network

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Whole Genome Gene Discovery in the Pathogenic Oomycete Pythium insidiosum by 454 Sequencing Technology

Whole Genome Gene Discovery in the Pathogenic Oomycete Pythi...

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The Annual Oomycete Molecular Genetics Network Meeting(国际卵菌分子遗传学年会)

作者： Theerapong Krajaejun Shoba Ranganathan Rommanee Khositnithikul Tassanee Lerksuthirat Tassanee Lowhnoo Thidarat Rujirawat Wanta Yingyong Prapat Suriyaphol Sittichoke Tangphatsornruang Gagan Garg Department of Pathology Mahidol University Bangkok Department of Chemistry and Biomolecular Sciences Macquarie University Australia Molecular Medicine Program Multidisciplinary Unit Faculty of Science Mahidol University Bangkok Research Center Faculty of Medicine Ramathibodi HospitalMahidol University Bangkok Bioinformatics and Data Management for Research Office for Research and Development Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Genome Sequencing Laboratory National Center for Genetic Engineering and Biotechnology National Science and Technology Development Agency PathumthaniThailand

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data decomposition in biomedical e-Science applications

Data decomposition in biomedical e-Science applications

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7th IEEE International Conference on e-Science Workshops, eScienceW 201

作者： Mohammed, Yassene Shahand, Shayan Korkhov, Vladimir Luyf, Angela C.M. Van Schaik, Barbera D.C. Caan, Matthan W.A. Van Kampen, Antoine H.C. Palmblad, Magnus Olabarriaga, Silvia D. Bioinformatics Laboratory Department of Clinical Epidemiology Biostatistics and Bioinformatics University of Amsterdam Netherlands Biomolecular Mass Spectrometry Unit Department of Parasitology Leiden University Medical Center Netherlands Regional Computing Center for Lower Saxony and L3S University of Hannover Germany Faculty of Applied Math and Control Processes St. Petersburg State University Russia Department of Radiology AMC University of Amsterdam Netherlands Biosystems Data Analysis Swammerdam Institute for Life Sciences University of Amsterdam 1098 XH Amsterdam Netherlands

ISBN: (纸本)9780769545981

As the focus of e-Science is moving toward the forth paradigm and data intensive science, data access remains dependent on the architecture of the used e-Science infrastructure. Such architecture is in general job-driven, i.e., a (grid) job is a sequence of commands that run on the same worker node. Making use of the infrastructure involves having a parallelized application. This is done foremost by data decomposition. In general practice of parallel programming, data decomposition depends on the programmer's experience and knowledge about the used data and the algorithm/application. On the other hand, data mining scientists have an established foundation for data decomposition, automatic decomposition methods are already in use, methodologies and patterns are defined. Our experience in porting biomedical applications to the Dutch e-Science infrastructure shows that the used data decomposition to gain parallelism fit to some degree a subgroup of the data mining decomposition patterns, i.e., object set decomposition. In this paper we discuss porting three biomedical packages to a grid computing environment, two for medical imaging and one for DNA sequencing. We show how the data access of the applications was reengineered around the executables to make use of the parallel capacity of e-Science infrastructure. © 2011 IEEE.

关键词： Grid computing

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Dynamic remodeling of context-specific miRNAs regulation networks facilitate in silico cancer drug screening

Dynamic remodeling of context-specific miRNAs regulation net...

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IEEE International Conference on Systems Biology

作者： Lida Zhu Fengji Liang Juan Liu Simon Rayner Yinghui Li Shanguang Chen Jianghui Xiong School of Computer Science Wuhan University Wuhan China Bioinformatics Group and Data Coordination Center State Key Laboratory of Space Medicine Fundamentals and Application (SMFA) China Astronaut Research and Training Center Beijing China Bioinformatics Group State Key Laboratory of Virology Wuhan Institute of Virology Chinese Academy of Sciences (CAS) Wuhan China

Background: Much effort has been expended in exploring the connections between transcriptome, disease and drug, based on the premise that drug induced perturbations in the transcriptome will affect the phenotype and finally help to cure a disease. MicroRNAs (miRNAs) play a key role in the regulation of the transcriptome and have been identified as a key mediator in human disease and drug response. However, even if miRNA expression can be precisely detected, the information regarding miRNAs action on a particular part of the transcriptome is still lacking. Here, we introduced a novel concept, the Context-specific MiRNA activity (CoMi activity), to reflect a miRNA's regulation effect on a context specific gene set, by calculating the statistical difference between the distributions of its target gene expression and non-target gene expression. In this study we investigate whether CoMi activity could provide a novel perspective on miRNA mechanisms of action in disease and drug response, and facilitate in silico drug screening. Results: Using breast cancer as an example, we examined the CoMi activity based on a Gene Ontology (GO) term as context. Then we constructed a differential CoMi activity network (cancer vs. normal), based on the comi activity represents as a link between miRNAs and GO terms, (e.g. hsa-miR-27a's regulation on GO term "apoptosis"). The topological analysis of the generated network demonstrated that the cancer specific CoMi network is a scale free network. The highly connected nodes highlighted a group of known onco-miRNAs (e.g. hsa miR-183*) and tumor suppressor miRNAs (e.g. hsa-miR-34a), as well as some well-known cancer related GO biological processes (e.g. apoptosis). Interestingly, we found that chemotherapeutic drug treatment can counteract the dis regulated CoMi activity in the cancer-specific network. For instance, 100% of down-regulated CoMi activities in a "core" breast cancer network contains apoptosis-related GO terms that could be counte

关键词： Drugs Gene expression Breast cancer Libraries Silicon Indexes

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