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第八届中国蛋白质组学大会

作者： Peng Li Jean Thierry-Mieg Baitang Ning James C Fuscoe Qi Lv Pengzhan Hu Ruichao Xue Christopher Mason Altuna Akalin Geng Chen Chen Zhao Weida Tong Huixiao Hong Lei Guo Hong Fang Tao Qing Ying Yu Wenzhong Xiao Danielle Thierry-Mieg Leming Shi Tieliu Shi Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China National Center for Biotechnology InformationNational Library of MedicineNIHBethesdaMD 20894USA National Center for Toxicological ResearchFood and Drug AdministrationJeffersonARUSA Department of PhysiologyBiophysicsand Systems BiologyTri-Institutional Program(CornellSloan-Ketteringand Rockefeller)on Medicine1305 York AveUSA Center for PharmacogenomicsSchool of PharmacyFudan UniversityShanghaiChina Massachusetts General HospitalHarvard Medical School51 Blossom StBostonMA 02114USA National Center for Toxicological ResearchFood and Drug AdministrationJeffersonARUSA Center for Pharmacogenomics School of PharmacyFudan UniversityShanghaiChina

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71 Genomic regions flanking E-box binding sites influence DNA binding specificity of bHLH transcription factors through DNA shape

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Journal of Biomolecular Structure and Dynamics 2013年第SUPP 1期31卷 45-46页

作者： Raluca Gordan[a][b][*] Ning Shen[c] Iris Dror[d] Tianyin Zhou[d] John Horton[b] Remo Rohs[d] & Martha L. Bulyk[e][f] [a] Departments of Biostatistics and Bioinformatics Computer Science and Molecular Genetics and Microbiology Duke University Durham NC USA [b] Institute for Genome Sciences and Policy Duke University Durham NC 27708 USA Phone: Phone: +1 (919) 667-8673 Fax: Phone: +1 (919) 667-8673 [c] Department of Pharmacology and Cancer Biology Duke University Durham NC 27708 USA [d] Molecular and Computational Biology Program Departments of Biological Sciences Chemistry and Physics and Astronomy University of Southern California 1050 Childs Way Los Angeles CA 90089 USA [e] Division of Genetics Departments of Medicine and Pathology Brigham and Women’s Hospital and Harvard Medical School Boston MA 02115 USA [f] Harvard-MIT Division of Health Sciences and Technology (HST) Harvard Medical School Boston MA 02115 USA

Transcriptional regulation of gene expression is enacted mainly through binding of transcription factors (TFs) to specific, short DNA sites in cis-regulatory regions of genes. Most TFs are members of protein families that share a common DNA-binding domain and thus recognize similar DNA-binding sequences. It is not well understood why paralogous TFs often bind different genomic target sitesin vivoto effect different regulatory programs, despite apparently recognizing the same sequence motifs. Here, we designed custom protein-binding microarrays (PBMs) to analyze the DNA-binding specificities of twoSaccharomyces cerevisiaebasic helix-loop-helix (bHLH) proteins, Tye7 and Cbf1, as a model system. Our data reveal that E-box DNA-binding sequences (CAnnTG), when tested in the context of their native genomic flanking sequences, are bound differently by Cbf1 and Tye7. computational models of the PBM data indicate that DNA sequence features located in the genomic sequences outside the E-box contribute to DNA-binding specificityin vitro. Our analyses suggest that these flanking regions affect DNA-binding specificity indirectly by influencing the three-dimensional structure of the E-box binding sites. Finally, we show that these subtle differences in intrinsic sequence preferences of Cbf1 and Tye7in vitrohelp to explain their differential DNA-binding preferencesin vivo. Our results provide further evidence that the local shape of DNA-binding sites may be an important feature in distinguishing the DNA-binding preferences among paralogous TFs and thus may play a widespread role in determining how transcriptional regulatory specificity within TF families is achieved.

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2640 – Exploring the pathogenetic association between schizophrenia and type 2 diabetes mellitus diseases based on pathway analysis

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European Psychiatry 2013年第S1期28卷 1-1页

作者： Liu, Y. Li, Z. Yi, Z. Shi, T. Center for Bioinformatics and Computational Biology Institute of Biomedical Sciences School of Life Sciences East China Normal University Department of Neurology Shanghai Changhai Hospital Secondary Military Medical University Schizophrenia Program Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine Shanghai China

Accumulated studies indicate that schizophrenia patients are prone to present the type 2 diabetes symptoms, but the potential mechanisms behind their association remain unknown. Here we explored the pathogenetic association between SCZ and T2D based on pathway analysis and protein-protein interaction. To explore the pathway crosstalk, we constructed a pathway-based network including all of those significant pathways. Our results revealed that some pathways are shared by both SCZ and T2D diseases through a number of susceptibility genes. With 382 unique susceptibility proteins for SCZ and T2D, we further built a protein-protein interaction network by extracting their nearest interacting neighbours. Among 2,104 retrieved proteins, 364 of them were found simultaneously interacted with susceptibility proteins of both SCZ and T2D, and proposed as new candidate risk factors for both diseases. Moreover, some proteins were hub proteins with high connectivity and interacted with multiple proteins involved in both *** of these hub proteins are the components of our identified enriched pathways, including calcium signaling, g-secretase mediated ErbB4 signaling, adipocytokine signaling, insulin signaling, AKT signaling and type II diabetes mellitus pathways. Through the integration of multiple lines of information, we proposed that those signaling pathways, such as AKT signaling, that contain susceptibility genes for both diseases, could be the key pathways to bridge SCZ and T2D. AKT could be one of the important shared components and may play a pivotal role to link both of the pathogenetic processes. Our study provides the general pathway-based view of pathogenetic association between two diseases.

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Deciphering sequence and structure features of disease-causing small insertions and deletions

Deciphering sequence and structure features of disease-causi...

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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： Xinjun Zhang Huiying Zhao Yadong Wang Guohua Wang Yaoqi Zhou Yunlong Liu School of Computer Sciences and Technology Harbin Institute of Technology Harbin Heilongjiang 150001 China School of Informatics and Computing Indiana University Bloomington IN 47408 USA School of Computer Sciences and Technology Harbin Institute of Technology Harbin Heilongjiang 150001 China Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indianapolis IN 46202 USA Bioinformatics program School of Informatics Indiana University Purdue University Indianapolis Indianapolis IN 46202 USA Department of Medical and Molecular Genetics Indiana University School of Medicine Indianapolis IN 46202 USA Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indianapolis IN 46202 USA Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indianapolis IN 46202 USA

Background: Small insertions and deletions (INDELs) compose of the second largest category of genetic variants (next to single nucleotide polymorphism) in the human genome, which accounts for 18% of all the variants *** from the 1,000 Genome Project indicated an estimate of 1 million INDELs per human *** to SNPs (Single Nucleotide Polymorphisms) and large structural variations, INDELs are of significant interest due to their potentials in affecting gene molecular functions and therefore cause *** of its functional importance, lacking a highly accurate bioinformatics tool for INDEL classifications has become a major obstacle in understanding the molecular ***: In this study, we develop a bioinformatics tool for INDEL *** constructed a training dataset that includes all the disease-causing and neutral INDELs documented in the Human Genome Mutation Database (HGMD) and 1,000 Genome *** the two sets of INDELs, we systematically investigated a series of features on their potentials in disrupting both protein structures and pre-mRNA *** then designed a predictor to best distinguish the disease-causing and neutral INDELs using machine-learning ***: In this study, we focused on the disease relevance of the INDELs in the exonic regions, which include 25,923 and 4,643 disease-causing and neutral INDELs, *** found that the disease-causing INDELs more likely occur in predicted structured regions and neutral INDELs are more likely in unstructured, intrinsically disordered *** also found that INDEL sites matched more to homologous sequences are more like *** RNA processing, we found disease-causing INDELs are twice likely to disrupt binding sites of RNA-binding *** also found that disease-causing INDELs tend to be longer, and be closer to the splice *** addition, the genomic loci for disease-causing INDELs are more evolutionarily conserved, a

关键词： insertion deletions INDELs genetic variants next generation sequencing

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103 Probing DNA shape and methylation state on a genomic scale with DNase I

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Journal of Biomolecular Structure and Dynamics 2013年第SUPP 1期31卷 65页

作者： Allan Lazarovici[a][b] Tianyin Zhou[c] Anthony Shafer[d] Ana Carolina Dantas Machado[c] Richard Sandstrom[d] Peter J. Sabo[d] Yan Lu[c] Remo Rohs[c] John A. Stamatoyannopoulos[d] & Harmen J. Bussemaker[b][e][*] [a] Department of Electrical Engineering Columbia University New York NY 10027 USA [b] Department of Biological Sciences Columbia University New York NY 10027 USA [c] Molecular and Computational Biology Program Departments of Biological Sciences Chemistry and Physics and Astronomy University of Southern California Los Angeles CA 90089 USA [d] Departments of Genome Sciences and Medicine University of Washington Seattle WA 98195 USA [e] Center for Computational Biology and Bioinformatics Columbia University New York NY 10032 USA Phone: Phone: (212) 854-9932 Fax: Phone: (212) 854-9932

DNA binding proteins find their cognate sequences within genomic DNA through recognition of specific chemical and structural features. Here, we demonstrate that high-resolution DNase I cleavage profiles can provide detailed information about the shape and chemical modification status of genomic DNA. Analyzing millions of DNA-backbone hydrolysis events on naked genomic DNA, we show that the intrinsic rate of cleavage by DNase I closely tracks the width of the minor groove. Integration of these DNase I cleavage data with bisulfite sequencing data for the same cell type genome reveals that the cleavage directly adjacent to CpG dinucleotides is enhanced at least eight-fold by cytosine methylation. This phenomenon we show is attributable to methylation-induced narrowing of the minor groove. Furthermore, we demonstrate that it enables simultaneous mapping of DNase I hypersensitivity and regional DNA methylation levels using densein vivocleavage data. Taken together, our results suggest a general mechanism through which CpG methylation can modulate protein–DNA interaction strength via the remodeling of DNA shape.

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Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) : Jeddah, Kingdom of Saudi Arabia. 30 November - 3 December 2015

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BMC genomics 2016年第6期17 Suppl 6卷 487页

作者： Jerry W. Shay Noriko Homma Ruyun Zhou Muhammad Imran Naseer Adeel G. Chaudhary Mohammed Al-Qahtani Nobutaka Hirokawa Maryam Goudarzi Albert J. Fornace Saleh Baeesa Deema Hussain Mohammed Bangash Fahad Alghamdi Hans-Juergen Schulten Angel Carracedo Ishaq Khan Hanadi Qashqari Nawal Madkhali Mohamad Saka Kulvinder S. Saini Awatif Jamal Jaudah Al-Maghrabi Adel Abuzenadah Adeel Chaudhary Mohammed Al Qahtani Ghazi Damanhouri Heba Alkhatabi Anne Goodeve Laura Crookes Nikolas Niksic Nicholas Beauchamp Adel M. Abuzenadah Jim Vaught Bruce Budowle Mourad Assidi Abdelbaset Buhmeida Leena Merdad Sudhir Kumar Sayaka Miura Karen Gomez Mahmood Rasool Ahmed Rebai Sajjad Karim Hend F. Nour Eldin Heba Abusamra Elham M. Alhathli Nada Salem Mohammed H. Al-Qahtani Hossam Faheem Ashok Agarwa Eberhard Nieschlag Joachim Wistuba Oliver S. Damm Mohd A. Beg Taha A. Abdel-Meguid Hisham A. Mosli Osama S. Bajouh Serdar Coskun Muhammad Abu-Elmagd Ashraf Dallol Sahar Hakamy Wejdan Al-Qahtani Asia Al-Harbi Shireen Hussain Burak Ozkosem Rick DuBois Safia S. Messaoudi Maryam T. Dandana Touhami Mahjoub Wassim Y. Almawi S. Abdalla M. Nabil Al-Aama Asmaa Elzawahry Tsuyoshi Takahashi Sachiyo Mimaki Eisaku Furukawa Rie Nakatsuka Isao Kurosaka Takahiko Nishigaki Hiromi Nakamura Satoshi Serada Tetsuji Naka Seiichi Hirota Tatsuhiro Shibata Katsuya Tsuchihara Toshirou Nishida Mamoru Kato Sajid Mehmood Naeem Mahmood Ashraf Awais Asif Muhammad Bilal Malik Siddique Mehmood Aadil Hussain Qazi Mohammad Sajid Jamal Mughees Uddin Siddiqui Mohammad A. Alzohairy Mohammad A. Al Karaawi Taoufik Nedjadi Heba Al-Khattabi Adel Al-Ammari Ahmed Al-Sayyad Hédia Zitouni Nozha Raguema Marwa Ben Ali Wided Malah Raja Lfalah Wassim Almawi Mohammed Elanbari Andrey Ptitsyn Sana Mahjoub Rabeb El Ghali Bechir Achour Nidhal Ben Amor Brahim N’siri Hamid Morjani Esam Azhar Vera Chayeb Maryam Dendena Hedia Zitouni Khedija Zouari-Limayem Bassem Refaat Ahmed M. Ashshi Sarah A. Batwa Hazem Ramadan Amal Awad Ahmed Ateya Adel Galal Ahmed El-Shemi Ahmad Ashshi Mohammed Basalamah Youjin Na Cha University of Texas Southwestern Medical Center Dallas USA Department of Cell Biology and Anatomy Graduate School of Medicine the University of Tokyo Tokyo Japan Center of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Department of Biochemistry and Molecular & Cellular Biology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Radiation Medicine Lombardi Comprehensive Cancer Center Georgetown University Washington USA Center of Excellence in Genomic Medicine Research (CEGMR) King Abdulaziz University Jeddah Kingdom of Saudi Arabia King Fahd Medical Research Centre King Abdulaziz University Jeddah Saudi Arabia Centre of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Sheffield Diagnostic Genetic Service Sheffield Children’s NHS Foundation Trust Western Bank Sheffield UK Center of Innovations in Personalized Medicine King Abdulaziz University Jeddah Saudi Arabia President ISBER Editor-in-Chief Biopreservation & Biobanking ᅟ USA Institute of Applied Genetics Department of Molecular and Medical Genetics University of North Texas Health Science Center Fort Worth USA Department of Dental Public Health Faculty of Dentistry King Abdulaziz University Jeddah Saudi Arabia Institute for Genomics and Evolutionary Medicine Temple University Philadelphia USA Center of Excellence in Genomic Medicine King Abdulaziz University Jeddah Kingdom of Saudi Arabia Laboratory of Molecular and Cellular Screening Processes (Bioinformatics Group) Centre of Biotechnology of Sfax Sfax Tunisia Fujitsu Technology Solutions International ᅟ ᅟ Case Western Reserve University School of Medicine and Lerner College of Medicine Cleveland Clinic Foundation Cleveland USA American Center for Reproductive Medicine Andrology Center Cleveland USA Center for Reproductive Medicine and

O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic me

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SYSTEMS biology IN BARLEY POWDERY MILDEW INTERACTIONS

SYSTEMS BIOLOGY IN BARLEY POWDERY MILDEW INTERACTIONS

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The 13th International Cereal Rusts and Powdery Mildews Conference(第13届国际禾谷类锈病与白粉病大会)

作者： Roger WISE Priyanka SURANA Greg FUERST Ruo XU Dan NETTLETON Divya MISTRY Julie DICKERSON Lin WANG Tom BRUTNELL Department of Plant Pathology and Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011USA Department of Statistics Iowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate ProgramIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate ProgramIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011USA Department of Plant Pathology and MicrobiologyCenter for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011USA Crop and Insect Genetics Genomicsand Informatics Research UnitU.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011USA Department of Plant Pathology and Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011USA Department of StatisticsIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate ProgramIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011USA Crop and Insect GeneticsGenomicsand Informatics Research UnitU.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011USA Department of Electrical and Computer Engineering Iowa State UniversityAmesIowa 50011USA Boyce Thompson Institute for Plant ResearchCornell UniversityIthacaNY

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EQTL AND MUTATIONAL ANALYSIS OF NB-LRR MEDIATED IMMUNITY TO POWDERY MILDEW

EQTL AND MUTATIONAL ANALYSIS OF NB-LRR MEDIATED IMMUNITY TO ...

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The 13th International Cereal Rusts and Powdery Mildews Conference(第13届国际禾谷类锈病与白粉病大会)

作者： Roger WISE Priyanka SURANA Greg FUERST Ruo XU Divya MISTRY Julie DICKERSON Dan NETTLETON Department of Statistics Iowa State UniversityAmesIowa 50011 Department of Plant Pathology and Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011 Department of StatisticsIowa State UniversityAmesIowa 50011 Bioinformatics and Computational Biology Graduate ProgramIowa State UniversityAmesIowa 50011 Department of Electrical and Computer Engineering Iowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate ProgramIowa State UniversityAmesIowa 50011 Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011 Department of Plant Pathology and MicrobiologyCenter for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011 Department of Plant Pathology and Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011 Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011 Crop and Insect GeneticsGenomicsand Informatics Research UnitU.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011 Crop and Insect Genetics Genomicsand Informatics Research UnitU.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011

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Deciphering sequence and structure features of disease-causing small insertions and deletions

Deciphering sequence and structure features of disease-causi...

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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： Xinjun Zhang Huiying Zhao Yadong Wang Guohua Wang Yaoqi Zhou Yunlong Liu School of Informatics and Computing Indiana UniversityBloomingtonIN47408USA Center for Computational Biology and Bioinformatics Indiana University School of MedicineIndianapolisIN 46202USA Bioinformatics program School of InformaticsIndiana University Purdue University IndianapolisIndianapolisIN 46202USA School of Computer Sciences and Technology Harbin Institute of Technology Department of Medical and Molecular Genetics Indiana University School of MedicineIndianapolisIN 46202USA

Background:Small insertions and deletions(INDELs) compose of the second largest category of genetic variants(next to single nucleotide polymorphism) in the human genome, which accounts for 18%of all the variants *** from the 1,000 Genome Project indicated an estimate of 1 million INDELs per human *** to SNPs(Single Nucleotide Polymorphisms) and large structural variations,INDELs are of significant interest due to their potentials in affecting gene molecular functions and therefore cause *** of its functional importance,lacking a highly accurate bioinformatics tool for INDEL classifications has become a major obstacle in understanding the molecular functions. Methods:In this study,we develop a bioinformatics tool for INDEL *** constructed a training dataset that includes all the disease-causing and neutral INDELs documented in the Human Genome Mutation Database(HGMD) and 1,000 Genome *** the two sets of INDELs,we systematically investigated a series of features on their potentials in disrupting both protein structures and pre-mRNA *** then designed a predictor to best distinguish the disease-causing and neutral INDELs using machine-learning technique. Results:In this study,we focused on the disease relevance of the INDELs in the exonic regions,which include 25,923 and 4,643 disease-causing and neutral INDELs,*** found that the disease-causing INDELs more likely occur in predicted structured regions and neutral INDELs are more likely in unstructured,intrinsically disordered *** also found that INDEL sites matched more to homologous sequences are more like *** RNA processing, we found disease-causing INDELs are twice likely to disrupt binding sites of RNA-binding proteins. We also found that disease-causing INDELs tend to be longer,and be closer to the splice *** addition,the genomic loci for disease-causing INDELs are more evolutionarily conserved,and tend to locat

关键词： insertion deletions INDELs genetic variants next generation sequencing

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A Bayesian model for SNP discovery based on next-generation sequencing data

A Bayesian model for SNP discovery based on next-generation ...

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IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

作者： Yanxun Xu Xiaofeng Zheng Yuan Yuan Marcos R Estecio Jean-Pierre Issa Yuan Ji Shoudan Liang Department of Statistics Rice University Houston TX USA Department of Bioinformatics and Computational Biology University of Texas M.D. Anderson Cancer Center Houston TX USA Graduate Program in Structural and Computational Biology and Molecular Biophysics Baylor College of Medicine Houston TX USA Department of Biochemistry and Molecular Biology University of Texas M.D. Anderson Cancer Center Houston TX USA Fels Institute for Cancer Research and Molecular Biology Temple University Philadelphia PA USA CCRI NorthShore University HealthSystem Chicago IL USA

ISBN: (纸本)9781467352345

A single-nucleotide polymorphism (SNP) is a single base change in the DNA sequence and is the most common polymorphism. Since some SNPs have a major influence on disease susceptibility, detecting SNPs plays an important role in biomedical research. To take fully advantage of the next-generation sequencing (NGS) technology and detect SNP more effectively, we propose a Bayesian approach that computes a posterior probability of hidden nucleotide variations at each covered genomic position. The position with higher posterior probability of hidden nucleotide variation has a higher chance to be a SNP. We apply the proposed method to detect SNPs in two cell lines: the prostate cancer cell line PC3 and the embryonic stem cell line H1. A comparison between our results with dbSNP database shows a high ratio of overlap (≥95 %). The positions that are called only under our model but not in dbSNP may serve as candidates for new SNPs.

关键词： comparison candidates generation Single nucleotide polymorphism sequence number protection a posteriori probability DNA Sequence Bayesian inference Disease Susceptibility Analyses, Sequence

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