...D38–D51 Nucleic Acids Research, 2011, Vol. 39, Database issue doi:10.1093/nar/gkq1172 Published online 20 November 2010 Database resources of the National Center for Biotechnology Information Eric W. Sayers1,*, Tanya Barrett1, Dennis A. Benson1, Evan Bolton1, Stephen H. Bryant1, Kathi Canese1, Vyacheslav Chetvernin1, Deanna M. Church1, Michael DiCuccio1, Scott Federhen1, Michael Feolo1, Ian M. Fingerman1, Lewis Y. Geer1, Wolfgang Helmberg2, Yuri Kapustin1, David Landsman1, David J. Lipman1, Zhiyong Lu1, Thomas L. Madden1, Tom Madej1, Donna R. Maglott1, Aron Marchler-Bauer1, Vadim Miller1, Ilene Mizrachi1, James Ostell1, Anna Panchenko1, Lon Phan1, Kim D. Pruitt1, Gregory D. Schuler1, Edwin Sequeira1, Stephen T. Sherry1, Martin Shumway1, Karl Sirotkin1, Douglas Slotta1, Alexandre Souvorov1, Grigory Starchenko1, Tatiana A. Tatusova1, Lukas Wagner1, Yanli Wang1, W. John Wilbur1, Eugene Yaschenko1 and Jian Ye1 1 Downloaded from http://nar.oxfordjournals.org/ by guest on March 20, 2015 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Building 38A, 8600 Rockville Pike, Bethesda, MD 20894, USA and 2University Clinic of Blood Group Serology and Transfusion Medicine, Medical University of Graz, Auenbruggerplatz 3, A-8036 Graz, Austria Received September 16, 2010; Revised October 29, 2010; Accepted November 1, 2010 ABSTRACT In addition to maintaining the GenBank nucleic acid sequence database, the National Center for Biotechnology...
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...in Bioinformatics for Genomics and Drug Design Bioinformatics is essential to give meaning to the huge mass of biological data that is being produced in the post-genomic era, playing a prominent role in the biomedical and biotechnological research of this century. Bioinformaticians are highly qualified and demanded professionals. They enjoy many positions available on leading research fields as genomics, personalized medicine, drug discovery, biotechnology, crop improvement and other health science research fields. Program strengths The Master of Science in Bioinformatics for Genomics and Drug Design is a novel learning experience that differs from conventional programs in several ways: • Intensive one-year master’s program (60 ECTS). • International degree program. All classes are taught in English. • Highly practical orientation. The MSc in Bioinformatics provides training to create bioinformatics professionals ready to succeed. • Focus on three expertise areas. Genomics, Drug Discovery and High Performance Computing. • Highly qualified faculty. Faculty are leaders of international research groups and prestigious professionals from bioinformatics industry. • Student mentoring programs. • Bioinformatics resources. • Networking and job vacancies. Open positions offered by research groups and companies. • Financial aid may be provided. MSc in Bioinformatics for Genomics and Drug Design Program content and structure Module 1 Programming in Bioinformatics (6 ECTS)...
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...INDEX 1.To retrieve the protein or DNA sequence in FASTA format from the NCBI database and analyze the obtained data. 2.For a given protein sequences find the function ,structural relevance and annotation studies by using Uniprot/Uniprot KB. 3.For a given protein, find the protein PDB code ,release date , resolution ,Classification and pub med citation from PDB Structure data base. 4.Find the disease pathway ,drug target enzymes and drug molecules used for a given disease by using KEGG database. 5.For a given protein/enzyme find its EC number ,its location and Km, K cat/Km values by using BRENDA/KEGG database. 6.Find the pair wise sequence alignment for a given protein/DNA sequence by using Dot matrix method Dot helix and comment on the results inverted repeats ,palindromes. 7.For a given Protein sequence find the homolog sequences and Study the obtained output critical statistical parameters, the % identity, %similarity ,p ,E-value by using BLAST. 8.For a given Protein/DNA sequence find the pblast ,nblast ,psi blast ,phi blast ,blast, tbalstn and analyze the obtained results obtained results for each blast method. 9.For a given Protein sequence find the pair wise sequence alignment by using the FASTA algorithm and compare the results obtained with those from other methods. 10.Find the optimal alignment for the given protein sequence by using Dynamic programming –LALIGN method. 11.For a given FASTA sequence find the multiple sequence alignment by using the Clustal...
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...CURRICULUM VITAE NAME: BERNARD NDINI MWENDWA PHONE NUMBER: 0789921182/ 0707343489/0727609248 E-MAIL: benardmwendwa.bm@gmail.com/benardndini@yahoo.com ADDRESS: 16-90214 DOB: 11/7/1992 GENDER: MALE NATIONALITY: KENYAN ID NUMBER: 29808279 RELIGION: CHRISTIAN MARITAL STATUS: SINGLE LANGUAGES: ENGLISH, KISWAHILI (both spoken and written) SUMMARY A hard-working and motivated BSC Biochemistry and Molecular Biology graduate with proven communication, organization and numeracy skills seeking to gain relevant experience to diversify and excel in varying fields. Looking to apply solid knowledge of biochemistry and molecular biology practices to setting and building on skills developed during course work studies. Eager to share the knowledge I have gained. Pro-active and keen to learn, ready to back up the knowledge I have gained with relevant experience .Wishing to make a positive contribution to production and research institutions. EDUCATION BACKGROUND 2012-2015: BSC BIOCHEMISTRY (MOLECULAR BIOLOGY) JOMO KENYATTA UNIVERSITY OF AGRICULTURE AND TECHNOLOGY, SECOND CLASS HONOURS (UPPER DIVISION) Jan 2007 –Nov 2010: KENYA CERTIFICATE OF SECONDARY EDUCATION St JOSEPH’S MUTITO BOYS SECONDARY SCHOOL GRADE ATTAINED:...
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...Homology modeling .Discuss (25) The advent of high throughput technologies such as next generation sequencing has led to generation of a lot of biological data which include protein sequences data. The full understanding of the biological roles of protein requires the knowledge of their structures. Experimental protein structure prediction methods consisting of x-ray crystallography and NMR spectroscopy are time consuming leaving a gap between generation of sequences and structure prediction. Computational approaches can be used to develop protein structure models which can be used for rational design of biochemical experiments which include site directed mutagenesis, protein stability and functional analysis of proteins. There are three computational approaches to three dimensional structure prediction namely homology modeling, threading and ab initio prediction (Xong, 2006). Homology modeling (comparative modeling) is a computational protein structure modeling technique used to build three dimensional (3D) models of proteins of unknown structure ( the target) on the basis of a sequence similarity to proteins of known structure (the template). Two conditions must be met to build a useful model, the similarity between the target sequence and template must be detectable and a substantially correct alignment between the target and the template should be calculated. Homology modelling is possible because small changes in protein sequence result in small changes in its 3D structures...
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...1-16 Protein Motifs Protein motifs may be defined by their primary sequence or by the arrangement of secondary structure elements The term motif is used in two different ways in structural biology. The first refers to a particular amino-acid sequence that is characteristic of a specific biochemical function. An example is the so-called zinc finger motif, CXX(XX)CXXXXXXXXXXXXHXXXH, which is found in a widely varying family of DNA-binding proteins (Figure 1-49). The conserved cysteine and histidine residues in this sequence motif form ligands to a zinc ion whose coordination is essential to stabilize the tertiary structure. Conservation is sometimes of a class of residues rather than a specific residue: for example, in the 12-residue loop between the zinc ligands, one position is preferentially hydrophobic, specifically leucine or phenylalanine. Sequence motifs can often be recognized by simple inspection of the amino-acid sequence of a protein, and when detected provide strong evidence for biochemical function. The protease from the human immunodeficiency virus was first identified as an aspartyl protease because a characteristic sequence motif for such proteases was recognized in its primary structure. The second, equally common, use of the term motif refers to a set of contiguous secondary structure elements that either have a particular functional significance or define a portion of an independently folded domain. Along with the functional sequence motifs, the former are...
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...11300A Bioinformatics Homework 2 Nov. 17, 2015 1. Sequence Alignment Using Dynamic Programming (DP) There are two amino acid sequences, seq1: COELACANTH and seq2: PELICAN. Obtain the global alignment by using DP (the Needleman-Wunsch algorithm) . [pic] |λ |c |o |e |l |a |c |a |n |t |h | |λ |0 |-1 |-2 |-3 |-4 |-5 |-6 |-7 |-8 |-9 |-10 | |p |-1 |-1 |-2 |-3 |-4 |-5 |-6 |-7 |-8 |-9 |-10 | |e |-2 |-2 |-2 |-1 |-2 |-3 |-4 |-5 |-6 |-7 |-8 | |l |-3 |-3 |-3 |-2 |0 |-1 |-2 |-3 |-4 |-5 |-6 | |i |-4 |-4 |-4 |-3 |-1 |-1 |-2 |-3 |-4 |-5 |-6 | |c |-5 |-5 |-5 |-4 |-2 |-2 |0 |-1 |-2 |-3 |-4 | |a |-6 |-6 |-6 |-5 |-3 |-1 |-1 |1 |0 |-1 |-2 | |n |-7 |-7 |-7 |-6 |-4 |-2 |-2 |0 |2 |1 |0 | | 2. In this question you will use two different dot matrix analysis servers to analyze the sequence of the human low density lipoprotein receptor (NP_000518). You will run a dot matrix analysis of this protein against itself (which means you will need to enter its sequence in both boxes on the website). A. First use Dottup (http://mobyle.pasteur.fr/cgi-bin/portal.py?#forms::dottup). Set the word size to 2 (“word size” is basically the same as “window”). Using a word size of 2, the algorithm will scan a window of 2 amino acids and put one dot in the matrix when the two sequences have identical amino acids. Dottup has no threshold, so it is simpler than Dotmatcher. a) Print (or copy and paste) the output from Dottup and turn it in. B. Now use Dotmatcher ...
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...BIOL 4200 Bioinformatics DNA, RNA, and protein structure exercises; MEGA5 This summary exercise focuses on the survey of the databases of RNA and protein structures with the goal of searching these databases to identify DNA or protein sequences that might be appropriate for your class project. This exercise will also start the phylogenetic analysis of DNA and protein sequences using MEGA5 Name: Sohaib Iqbal 1. Please click through these websites of RNA and protein structures. Please describe briefly what these websites are, in other words, what biological research activities you can conduct using these websites. Please rephrase your words, do not copy and paste, for any information you obtain from any other sources. Vienna RNA package: RNA Secondary Structure Prediction and Comparison http://www.tbi.univie.ac.at/RNA/ * This website shows research group bioinformatics and computational biology. This website represents the Institute of Theoretical Chemistry, which is a part of University of Vienna. They use and develop algorithms to detect RNA genes, folding dynamics of melecules, RNA design and chemical reaction networks. Vienna RNA webservers: http://rna.tbi.univie.ac.at/ * This page shows programs and web services that can be used to show and discuss RNA secondary structures. They also consist of folding kinetics, sequence design, and genome wide screening. tRNAscan-SE Search Server: http://lowelab.ucsc.edu/tRNAscan-SE/ * This website...
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...Name: CHEN LIN Student ID: 44141569-3 11300A Bioinformatics Homework 2 Nov. 18, 2014 1. Sequence Alignment Using Dynamic Programming (DP) There are two amino acid sequences, seq1: COELACANTH and seq2: PELICAN. Obtain the global alignment by using DP (the Needleman-Wunsch algorithm) . $+ 1 for letter that match ! Scoring scheme : #- 1 for mismatches !- 1 for gaps " Answer: ————————————————————————— C O E L A C A N T H P E L I C A N ————————————————————————— -1 -1 1 1 -1 1 1 1 -1 -1 λ λ P E L I C A N Seq1 Seq2 C -1 -1 -2 -3 -4 -3 -4 -5 O P O -2 -2 -2 -3 -4 -4 -4 -5 E E E -3 -3 -1 -2 -3 -4 -5 -5 L L L -4 -4 -2 0 -1 -2 -3 -4 A I A -5 -5 -3 -1 -1 -2 -1 -2 C C C -6 -6 -4 -2 -2 0 -1 -2 A A A -7 -7 -5 -3 -3 -1 1 0 N -8 -8 -6 -4 -4 -2 0 2 N N T -9 -9 -7 -5 -5 -3 -1 1 T — H -10 -10 -8 -6 -6 -4 -2 0 H — 0 -1 -2 -3 -4 -5 -6 -7 C — Name: CHEN LIN Student ID: 44141569-3 Seq1 Seq2 C P O — E E L L A I C C A A N N T — H — 2. In this question you will use two different dot matrix analysis servers to analyze the sequence of the human low density lipoprotein receptor (NP_000518). You will run a dot matrix analysis of this protein against itself (which means you will need to enter its sequence in both boxes on the website). A. First use Dottup (http://mobyle.pasteur.fr/cgi-bin/portal.py?#forms::dottup). Set the word size to 2 (“word size” is basically the same as “window”). Using a word size of 2, the algorithm will scan a window of 2 amino...
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...Human immunodeficiency virus (HIV) falls in a class of viruses called retroviruses. HIV is a virus infects by invading certain cells of immune system, specifically the white blood cells called T- helper lymphocytes or CD4 cells ,which normally activates other cells in the immune system to fight infection,. HIV. . Over the course of HIV infection, the immune system deteriorated since HIV kills T-helper lymphocytes and the body cannot fight the virus or subsequent infections. Thus, infected person becomes vulnerable to other secondary infections and cancer that are much rarer in healthy inviduals. Person with HIV infection are categorized as those living with HIV and those with acquired immunodeficiency syndrome (AIDS) diagnosis. An AIDS diagnosis is made when the presence of HIV is confirmed and the CD4 count drops below 200 cells/mL or after an AIDS indicator condition is diagnosed. Regimens of antiviral drugs can slow the immune system deterioriation in infected patients and extend the life expectancy of those who have developed AIDS. The most common serotype is HIV-1 which is distributed worldwide The RNA viruses which are retroviruses enters CD4 cells by binding to a specialized site which is receptor on a body cell. Then, the virus loses its protective coat and releases RNA, its genetic material , and an enzyme known as reverse transcriptase . The enzyme reverse transcriptase contained inside the viral core to convert their RNA into a form that can enter the...
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...Report on the connection between the Central dogma of Molecular Biology/ Bioinformatics, Model Organism and Drug Designing. The basis of the central dogma of molecular biology is the expression of the genetic information in any call. It is a universal process that occurs in every cell. The genetic information is stored in the DNA. During gene expression DNA is transcript to RNA and these RNA are transcribed to proteins. Bioinformatics deals with the genetic information which involves collecting, analyzing, manipulating and predicting etc. For the functioning of bioinformatics it is essential to know the genetic information that is stored in DNA. Therefore sequencing of DNA, genes or genomes is the fundamental need in bioinformatics. Organisms that are used in biological experiments in laboratories are called ‘model organisms’, of which most genomes are sequenced at present (rat, yeast, Arabidopsis; plant model organism) These sequenced genomes could be analyzed using bioinformatics tools in order to identify genes of significance as in drought tolerance genes in plants etc. Information revealed from sequencing could be studied using bioinformatics tools to understand its underlying mechanisms and to generate models that could be used in further studies. This information could also be used in evolutionary studies, micro array analysis, identification of genetic disorders (Alzheimer’s disease, breast cancer, cystic fibrosis, spinal muscular atrophy etc.) ...
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...Questions for Article 2 Seminar 2 What Does Bioinformatics Mean? To an Ailing Industrial Region, the Answer Is Jobs, by DAVID STABA – July 09, 2006. 1. Do you find it surprising that steel makers and manufacturers have left Buffalo? Do you find it surprising that the Trico Products Company moved operations to Mexico and Texas? Explain your answers in terms of comparative advantage. 2. Why might the U.S. have a comparative advantage in bioinformatics but not in manufacturing and steel making? 3. The article states "geneticists and researchers get trapped in looking at a very small question; they can have blinders on. Working with a clinician, you see the big picture" and that "scientists tend not to be very good at running a business, and a lot of times, not very interested in it". Explain these concepts in terms of specialization, trade, opportunity cost and comparative advantage. Answers 1. In relation to the theory of comparative advantage, steel makers and manufacturers may have found operations elsewhere to have a lower opportunity cost: workers and production processes elsewhere could be just as productive but with lower costs so that the savings could be used to expand the business, lower prices to match or beat those of competitors, increase profit or all of the above. 2. Steel making and many manufacturing industries are well established, ones that do not require much research and development. Bioinformatics is a new field that is driven by research and development...
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...said that extremely high or low pH’s denature an enzyme. By finding the specific pH at which amylase is most active, optimum production can be achieved. (Guyot et. al, 2000). In our experiment, we want to determine what pH levels is optimum for the enzymatic activity of amylase. To see if starch is broken down to glucose amylase, a spectrophotomer is used to see the amount of light that passed through. The more light that passes through the test tube means more starch was broken down into glucose. (Luesse, 2012). We hypothesized that the enzyme amylase will be most optimum around the pH of 7 and less active away from neutrality. Bioinformatics is an online database by which, scientists can look up any known protein sequence and protein function. It focuses on the sequence and structure of DNA, RNA, and protein. (Goto et. al., 1998). Using bioinformatics, you can take an unknown protein and compare its sequence to any known protein....
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...researcher in the Molecular Cell Physiology group at the Vrije Universiteit, Amsterdam. She has a PhD and MSc in Bioinformatics from the University of Manchester, and a BSc in Biochemistry from the University of Leeds. Katy’s work is primarily in the area of data and knowledge integration, where she leads the bioinformatics research activities in the myGrid consortium. myGrid is a UK e-Science initiative that has produced, amongst other things, the Taverna workflows workbench (http://www. taverna.org.uk/), the myExperiment workflow repository (http://www.myexperiment.org) and the BioCatalogue service catalogue (http://www. biocatalogue.org). Currently, her main focus is on the BBSRC funded SysMO SEEK project, to develop a data exchange and modelling environment for Systems Biology consortia in Europe (http://www.sysmo-db.org/). It was designed for the SysMO consortium, (Systems Biology of Micro-Organisms), but it has now been adopted by many other consortia, providing a common platform for hundreds of research labs in Europe. Katy also coordinates the training and outreach activities in myGrid. As such, she has been involved in teaching scientific workflows and related technologies in over 50 workshops, summer schools and conferences throughout the world. In this tutorial, she will provide an introduction to designing and reusing workflows for high-throughput bioinformatics data analysis, using Taverna and myExperiment. Scientific workflows enable the chaining together of distributed...
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...Open Access: Full open access to this and thousands of other papers at http://www.la-press.com. Evolutionary Bioinformatics Computational Identification of MicroRNAs from the Expressed Sequence Tags of Toxic Dinoflagellate Alexandrium Tamarense Dahai Gao1, limei Qiu1, Zhanhui Hou1, Qingchun Zhang2, Jianmin Wu3, Qiang Gao1 and linsheng song1 1 Key Laboratory of Experimental Marine Biology, Institute of Oceanology, Chinese Academy of Sciences (IOCAS), Qingdao, People’s Republic of China. 2Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences (IOCAS), Qingdao, People’s Republic of China. 3Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, People’s Republic of China. AbstrAct: Micro ribonucleic acids (miRNAs) represent a class of small noncoding RNAs that play important roles in multiple biological processes by degrading targeted mRNAs or by repressing mRNA translation. In the case of algal lineages, especially dinoflagellates, knowledge regarding the miRNA system is still limited and its regulatory role remains unclear. In the present study, a computational approach was employed to screen miRNAs from the expressed sequence tags (ESTs) of Alexandrium tamarense. A total of 18 potential miRNAs were identified according to a range of filtering criteria. In addition, unique evolutionary features, such as miRNA gene duplication and sequence similarity to metazoan miRNAs, implied that the...
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