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Nih definitions

on molecular

NIH – definitions

What is Bioinformatics? - Research, development, and application of computational tools and approaches for expanding the use of biological, medical, behavioral, and health data, including the means to acquire, store, organize, archive, analyze, or visualize such data.

What is Computational Biology? - The development and application of analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social data.


Nsf introduction
NSF – introduction

Large databases that can be accessed and analyzed with sophisticated tools have become central to biological research and education. The information content in the genomes of organisms, in the molecular dynamics of proteins, and in population dynamics, to name but a few areas, is enormous. Biologists are increasingly finding that the management of complex data sets is becoming a bottleneck for scientific advances. Therefore, bioinformatics is rapidly become a key technology in all fields of biology.


Nsf mission statement
NSF – mission statement

The present bottlenecks in bioinformatics include the education of biologists in the use of advanced computing tools, the recruitment of computer scientists into this evolving field, the limited availability of developed databases of biological information, and the need for more efficient and intelligent search engines for complex databases.


Nsf mission statement1
NSF – mission statement

The present bottlenecks in bioinformatics include the education of biologists in the use of advanced computing tools, the recruitment of computer scientists into this evolving field, the limited availability of developed databases of biological information, and the need for more efficient and intelligent search engines for complex databases.


Molecular bioinformatics
Molecular Bioinformatics

Molecular Bioinformatics involves the use of computational tools to discover new information in complex data sets (from the one-dimensional information of DNA through the two-dimensional information of RNA and the three-dimensional information of proteins, to the four-dimensional information of evolving living systems).


Bioinformatics (Oxford English Dictionary):

The branch of science concerned with information and information flow in biological systems, esp. the use of computational methods in genetics and genomics.


The field of science in which biology, computer science and information technology merge into a single discipline

Biologists

collect molecular data:

DNA & Protein sequences,

gene expression, etc.

Bioinformaticians

Study biological questions by analyzing molecular data

Computer scientists

(+Mathematicians, Statisticians, etc.)

Develop tools, softwares, algorithms to store and analyze the data.



The hereditary information of all living organisms, with the exception of some viruses, is carried by deoxyribonucleic acid (DNA) molecules.

2 purines:

2 pyrimidines:

adenine (A)

guanine (G)

cytosine (C)

thymine (T)

one ring

two rings


The entire complement of genetic material carried by an individual is called the genome.

Eukaryotes may have up to 3 subcellular genomes:

1. Nuclear

2. Mitochondrial

3. Plastid

Bacteria have either circular or linear genomes and may also carry plasmids

Human chromosomes

Circular genome


Central dogma: DNA makes RNA makes Protein individual is called the

Modified dogma: DNA makes DNA and RNA, RNA makes DNA, RNA an Protein


Amino acids individual is called the - The protein building blocks


Any region of the DNA sequence can, in principle, code for six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.


Protein folding six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

A human Hemoglobin:


How does it all looks like on a computer monitor? six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.


A cDNA sequence six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

>gi|14456711|ref|NM_000558.3| Homo sapiens hemoglobin, alpha 1 (HBA1), mRNA

ACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGCCGACAAGACCAACGTCAAGGCCGCCTGGGGTAAGGTCGGCGCGCACGCTGGCGAGTATGGTGCGGAGGCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGAAGGTGGCCGACGCGCTGACCAACGCCGTGGCGCACGTGGACGACATGCCCAACGCGCTGTCCGCCCTGAGCGACCTGCACGCGCACAAGCTTCGGGTGGACCCGGTCAACTTCAAGCTCCTAAGCCACTGCCTGCTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGGACAAGTTCCTGGCTTCTGTGAGCACCGTGCTGACCTCCAAATACCGTTAAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCCCTTCCTGCACCCGTACCCCCGTGGTCTTTGAATAAAGTCTGAGTGGGCGGC


A cDNA sequence (reading frame) six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

>gi|14456711|ref|NM_000558.3| Homo sapiens hemoglobin, alpha 1 (HBA1), mRNA

ACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGCCGACAAGACCAACGTCAAGGCCGCCTGGGGTAAGGTCGGCGCGCACGCTGGCGAGTATGGTGCGGAGGCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGAAGGTGGCCGACGCGCTGACCAACGCCGTGGCGCACGTGGACGACATGCCCAACGCGCTGTCCGCCCTGAGCGACCTGCACGCGCACAAGCTTCGGGTGGACCCGGTCAACTTCAAGCTCCTAAGCCACTGCCTGCTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGGACAAGTTCCTGGCTTCTGTGAGCACCGTGCTGACCTCCAAATACCGTTAAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCCCTTCCTGCACCCGTACCCCCGTGGTCTTTGAATAAAGTCTGAGTGGGCGGC

A protein sequence

>gi|4504347|ref|NP_000549.1| alpha 1 globin [Homo sapiens]

MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYR


And, a whole genome… six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

ACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGCCGACAAGACCAACGTCAAGGCCGCCTGGGGTAAGGTCGGCGCGCACGCTGGCGAGTATGGTGCGGAGGCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGAAGGTGGCCGACGCGCTGACCAACGCCGTGGCGCACGTGGACGACATGCCCAACGCGCTGTCCGCCCTGAGCGACCTGCACGCGCACAAGCTTCGGGTGGACCCGGTCAACTTCAAGCTCCTAAGCCACTGCCTGCTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGGACAAGTTCCTGGCTTCTGTGAGCACCGTGCTGACCTCCAAATACCGTTAAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCCCTTCCTGCACCCGTACCCCCGTGGTCTTTGAATAAAGTCTGAGTGGGCGGCACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGCCGACAAGACCAACGTCAAGGCCGCCTGGGGTAAGGTCGGCGCGCACGCTGGCGAGTATGGTGCGGAGGCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGAAGGTGGCCGACGCGCTGACCAACGCCGTGGCGCACGTGGACGACATGCCCAACGCGCTGTCCGCCCTGAGCGACCTGCACGCGCACAAGCTTCGGGTGGACCCGGTCAACTTCAAGCTCCTAAGCCACTGCCTGCTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGGACAAGTTCCTGGCTTCTGTGAGCACCGTGCTGACCTCCAAATACCGTTAAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCCCTTCCTGCACCCGTACCCCCGTGGTCTTTGAATAAAGTCTGAGTGGGCGGCACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGCCGACAAGACCAACGTCAAGGCCGCCTGGGGTAAGGTCGGCGCGCACGCTGGCGAGTATGGTGCGGAGGCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGAAGGTGGCCGACGCGCTGACCAACGCCGTGGCGCACGTGGACGACATGCCCAACGCGCTGTCCGCCCTGAGCGACCTGCACGCGCACAAGCTTCGGGTGGACCCGGTCAACTTCAAGCTCCTAAGCCACTGCCTGCTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGGACAAGTTCCTGGCTTCTGTGAGCACCGTGCTGACCTCCAAATACCGTTAAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCCCTTCCTGCACCCGTACCCCCGTGGTCTTTGAATAAAGTCTGAGTGGGCGGCGCCGTGGCGCACGTGGACGACATGCCCAACGCGCTGTCCGCCCTGAGCGACCTGCACGCGCACAAGCTTCGGGTGGACCCGGTCAACTTCAAGCTCCTAAGCCACTGCCTGCTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGGACAAGTTCCTGGCTTCTGTGAGCACCGTGCTGACCTCCAAATACCGTTAAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCCCTTCCTGCACCCGTACCCCCGTGGTCTTTGAATAAAGTCTGAGTGGGCGGCACTCTTCTGGTCCCCACAGACTCAGAGAGAACCCACCATGGTGCTGTCTCCTGCCGACAAGACCAACGTCAAGGCCGCCTGGGGTAAGGTCGGCGCGCACGCTGGCGAGTATGGTGCGGAGGCCCTGGAGAGGATGTTCCTGTCCTTCCCCACCACCAAGACCTACTTCCCGCACTTCGACCTGAGCCACGGCTCTGCCCAGGTTAAGGGCCACGGCAAGAAGGTGGCCG...


How big are whole genomes? six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

  • E. coli 4.6 x 106 nucleotides

    • Approx. 4,000 genes

  • Yeast 15 x 106 nucleotides

    • Approx. 6,000 genes

  • Human 3 x 109 nucleotides

    • Approx. 30,000 genes

  • Smallest human chromosome 50 x 106 nucleotides


What do we actually do with bioinformatics? six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.


Sequence assembly six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

(next generation sequencing)


Genome annotation six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.


Molecular evolution six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic

Smith et al. (2009) Nature 459, 1122-1125


Analysis of gene expression six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

Gene expression profile of relapsing versus non-relapsing Wilms tumors.

A set of 39 genes discriminates between the two classes of tumors.

(http://www.biozentrum2.uni-wuerzburg.de/, Prof. Gessler)


Analysis of regulation six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

Toledo and Bardot (2009) Nature 460, 466-467


Protein structure prediction six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

Protein docking


Luscombe, Greenbaum, Gerstein (2001) six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.


From dna to genome

Sanger sequences insulin protein six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

Watson and Crick DNA model

Dayhoff’s Atlas

Sequence alignment

ARPANET (early Internet)

PDB (Protein Data Bank)

Sanger dideoxy DNA sequencing

GenBank database

PCR (Polymerase Chain Reaction)

From DNA to Genome

1955

1960

1965

1970

1975

1980

1985


NCBI six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

SWISS-PROT database

FASTA

Human Genome Initiative

BLAST

EBI

World Wide Web

First bacterial genome

Yeast genome

First human genome draft

1990

1995

2000


Origin of bioinformatics and six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

biological databases:

The first protein sequence reported was that of bovine insulin in 1956, consisting of 51 residues.

Nearly a decade later, the first nucleic acid sequence was reported, that of yeast tRNAalanine with 77 bases.


In 1965, six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.Dayhoff gathered all the available sequence data to create the first bioinformatic database (Atlas of Protein Sequence and Structure).

The Protein DataBank followed in 1972 with a collection of ten X-ray crystallographic protein structures. The SWISSPROT protein sequence database began in 1987.


Nucleotides
Nucleotides six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.


Complete genomes
Complete Genomes six different amino acid sequences, because any one of three different reading frames can be used to interpret each of the two strands.

as of August2011:

Eukaryotes 37

Prokaryotes 1708

Total 1745



Open reading frames information?

Functional sites

Annotation

Structure, function


CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG information?

CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA

CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC

AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA

AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATG CAA

TAT GGA CAA TTG GTT TCT TCT CTG AAT ......

.............. TGAAAAACGTA


promoter information?

TF binding site

CCTGACAAATTCGACGTGCGGCATTGCATGCAGACGTGCATG

CGTGCAAATAATCAATGTGGACTTTTCTGCGATTATGGAAGAA

CTTTGTTACGCGTTTTTGTCATGGCTTTGGTCCCGCTTTGTTC

AGAATGCTTTTAATAAGCGGGGTTACCGGTTTGGTTAGCGAGA

AGAGCCAGTAAAAGACGCAGTGACGGAGATGTCTGATGCAA

TATGGACAATTGGTTTCTTCTCTGAAT .................................

..............TGAAAAACGTA

Transcription

Start Site

Ribosome binding Site

ORF = Open Reading Frame

CDS = Coding Sequence


Comparing ORFs information?

Identifying orthologs

Inferences on structure

and function

Comparative

genomics

Comparing functional sites

Inferences on regulatory

networks


Similarity profiles information?

Researchers can learned a great deal about the structure and function of human genes by examining their counterparts in model organisms.


Alignment preproinsulin information?

Xenopus MALWMQCLP-LVLVLLFSTPNTEALANQHL

Bos MALWTRLRPLLALLALWPPPPARAFVNQHL

**** : **.*: *:..* :. *:****

Xenopus CGSHLVEALYLVCGDRGFFYYPKIKRDIEQ

Bos CGSHLVEALYLVCGERGFFYTPKARREVEG

***************:******* :*::*

Xenopus AQVNGPQDNELDG-MQFQPQEYQKMKRGIV

Bos PQVG---ALELAGGPGAGGLEGPPQKRGIV

.**. *********

Xenopus EQCCHSTCSLFQLENYCN

Bos EQCCASVCSLYQLENYCN

*****.***:*******


Ultraconserved Elements in the Human Genome information?

Gill Bejerano, Michael Pheasant, Igor Makunin, Stuart Stephen, W. James Kent, John S. Mattick, & David Haussler (Science 2004. 304:1321-1325)

There are 481 segments longer than 200 base pairs (bp) that are absolutely conserved (100% identity with no insertions or deletions) between orthologous regions of the human, rat, and mouse genomes. Nearly all of these segments are also conserved in the chicken and dog genomes, with an average of 95 and 99% identity, respectively. Many are also significantly conserved in fish. These ultraconserved elements of the human genome are most often located either overlapping exons in genes involved in RNA processing or in introns or nearby genes involved in the regulation of transcription and development.

There are 156 intergenic, untranscribed, ultraconserved segments


Junk: information?

Supporting evidence

Junk is real!


Genome-wide profiling of: information?

• mRNA levels

• Protein levels

Co-expression of genes

and/or proteins

Functional

genomics

Identifying protein-protein interactions

Networks of interactions



Structural genome

genomics

Assign structure to all

proteins encoded in

a genome


Biological databases

Biological genomedatabases


Database or databank
Database or databank? genome

Initially

  • Databank (in UK)

  • Database (in the USA)

    Solution

  • The abbreviation db


What is a Database? genome

A structured collection of data held in computer storage; esp. one that incorporates software to make it accessible in a variety of ways; transf., any large collection of information.

database management: the organization and manipulation of data in a database.

database management system (DBMS): a software package that provides all the functions required for database management.

database system: a database together with a database management system.

Oxford Dictionary


What is a database
What is a database? genome

  • A collection of data

    • structured

    • searchable (index) -> table of contents

    • updated periodically (release) -> new edition

    • cross-referenced (hyperlinks) -> links with other db

  • Includes also associated tools (software) necessary for access, updating, information insertion, information deletion….

  • Data storage management: flat files, relational databases…


Database a flat file example
Database: a « flat file » example genome

Flat-file database («  flat file, 3 entries  »):

Accession number: 1

First Name: Amos

Last Name: Bairoch

Course: Pottery 2000; Pottery 2001;

//

Accession number: 2

First Name: Dan

Last name: Graur

Course: Pottery 2000, Pottery 2001; Ballet 2001, Ballet 2002

//

Accession number 3:

First Name: John

Last name: Travolta

Course: Ballet 2001; Ballet 2002;

//

  • Easy to manage: all the entries are visible at the same time !


Database a relational example
Database: a « relational » example genome

Relational database (« table file »):


Why biological databases
Why biological databases? genome

  • Exponential growth in biological data.

  • Data (genomic sequences, 3D structures, 2D gel analysis, MS analysis, Microarrays….) are no longer published in a conventional manner, but directly submitted to databases.

  • Essential tools for biological research. The only way to publish massive amounts of data without using all the paper in the world.


Distribution of sequences
Distribution of sequences genome

  • Books, articles 1968 -> 1985

  • Computer tapes 1982 -> 1992

  • Floppy disks 1984 -> 1990

  • CD-ROM 1989 ->

  • FTP 1989 ->

  • On-line services 1982 -> 1994

  • WWW 1993 ->

  • DVD 2001 ->


Some statistics
Some statistics genome

  • More than 1000 different ‘biological’ databases

  • Variable size: <100Kb to >20Gb

    • DNA: > 20 Gb

    • Protein: 1 Gb

    • 3D structure: 5 Gb

    • Other: smaller

  • Update frequency: daily to annually to seldom to forget about it.

  • Usually accessible through the web (some free, some not)


  • Some genomedatabases in the field of molecular biology…

  • AATDB, AceDb, ACUTS, ADB, AFDB, AGIS, AMSdb,

  • ARR, AsDb, BBDB, BCGD, Beanref, Biolmage,

  • BioMagResBank, BIOMDB, BLOCKS, BovGBASE,

  • BOVMAP, BSORF, BTKbase, CANSITE, CarbBank,

  • CARBHYD, CATH, CAZY, CCDC, CD4OLbase, CGAP,

  • ChickGBASE, Colibri, COPE, CottonDB, CSNDB, CUTG,

  • CyanoBase, dbCFC, dbEST, dbSTS, DDBJ, DGP, DictyDb,

  • Picty_cDB, DIP, DOGS, DOMO, DPD, DPlnteract, ECDC,

  • ECGC, EC02DBASE, EcoCyc, EcoGene, EMBL, EMD db,

  • ENZYME, EPD, EpoDB, ESTHER, FlyBase, FlyView,

  • GCRDB, GDB, GENATLAS, Genbank, GeneCards,

  • Genline, GenLink, GENOTK, GenProtEC, GIFTS,

  • GPCRDB, GRAP, GRBase, gRNAsdb, GRR, GSDB,

  • HAEMB, HAMSTERS, HEART-2DPAGE, HEXAdb, HGMD,

  • HIDB, HIDC, HlVdb, HotMolecBase, HOVERGEN, HPDB,

  • HSC-2DPAGE, ICN, ICTVDB, IL2RGbase, IMGT, Kabat,

  • KDNA, KEGG, Klotho, LGIC, MAD, MaizeDb, MDB,

  • Medline, Mendel, MEROPS, MGDB, MGI, MHCPEP5

  • Micado, MitoDat, MITOMAP, MJDB, MmtDB, Mol-R-Us,

  • MPDB, MRR, MutBase, MycDB, NDB, NRSub, 0-lycBase,

  • OMIA, OMIM, OPD, ORDB, OWL, PAHdb, PatBase, PDB,

  • PDD, Pfam, PhosphoBase, PigBASE, PIR, PKR, PMD,

  • PPDB, PRESAGE, PRINTS, ProDom, Prolysis, PROSITE,

  • PROTOMAP, RatMAP, RDP, REBASE, RGP, SBASE,

  • SCOP, SeqAnaiRef, SGD, SGP, SheepMap, Soybase,

  • SPAD, SRNA db, SRPDB, STACK, StyGene,Sub2D,

  • SubtiList, SWISS-2DPAGE, SWISS-3DIMAGE, SWISS-

  • MODEL Repository, SWISS-PROT, TelDB, TGN, tmRDB,

  • TOPS, TRANSFAC, TRR, UniGene, URNADB, V BASE,

  • VDRR, VectorDB, WDCM, WIT, WormPep, YEPD, YPD,

  • YPM, etc .................. !!!!


Categories of databases for life sciences
Categories of databases for Life Sciences genome

  • Sequences (DNA, protein)

  • Genomics

  • Mutation/polymorphism

  • Protein domain/family

  • Proteomics (2D gel, Mass Spectrometry)

  • 3D structure

  • Metabolic networks

  • Regulatory networks

  • Bibliography

  • Expression (Microarrays,…)

  • Specialized


NCBI: genomehttp://www.ncbi.nlm.nih.gov

EBI:http://www.ebi.ac.uk/

DDBJ:http://www.ddbj.nig.ac.jp/


Literature Databases: genome

Bookshelf: A collection of searchable biomedical books linked to PubMed.

PubMed: Allows searching by author names, journal titles, and a new Preview/Index option. PubMed database provides access to over 12 million MEDLINE citations back to the mid-1960's. It includes History and Clipboard options which may enhance your search session.

PubMed Central: The U.S. National Library of Medicine digital archive of life science journal literature.

OMIM: Online Mendelian Inheritance in Man is a database of human genes and genetic disorders (also OMIA).


Pubmed medline
PubMed (Medline) genome

  • MEDLINE covers the fields of medicine, nursing, dentistry, veterinary medicine, public health, and preclinical sciences

  • Contains citations from approximately 5,200 worldwide journals in 37 languages; 60 languages for older journals.

  • Contains over 20 million citations since 1948

  • Contains links to biological db and to some journals

  • New records are added to PreMEDLINE daily!



A search by subject: genome

“mitochondrion evolution”


Type in a query term
Type in a Query term genome

  • Enter your search words in the

    query box and hit the “Go” button

http://www.ncbi.nlm.nih.gov/entrez/query/static/help/helpdoc.html#Searching


The syntax
The Syntax … genome

  • Boolean operators: AND, OR, NOT must be entered in UPPERCASE (e.g., promoters OR response elements). The default is AND.

  • 2. Entrez processes all Boolean operators in a left-to-right sequence. The order in which Entrez processes a search statement can be changed by enclosing individual concepts in parentheses. The terms inside the parentheses are processed first. For example, the search statement: g1p3 OR (response AND element AND promoter).

  • 3. Quotation marks: The term inside the quotation marks is read as one phrase (e.g. “public health” is different than public health, which will also include articles on public latrines and their effect on health workers).

  • 4. Asterisk: Extends the search to all terms that start with the letters before the asterisk. For example, dia* will include such terms as diaphragm, dial, and diameter.


Refine the query
Refine the Query genome

  • Often a search finds too many (or too few) sequences, so you can go back and try again with more (or fewer) keywords in your query

  • The “History” feature allows you to combine any of your past queries.

  • The “Limits” feature allows you to limit a query to specific organisms, sequences submitted during a specific period of time, etc.

  • [Many other features are designed to search for literature in MEDLINE]


Related Items genome

  • You can search for a text term in sequence annotations or in MEDLINE abstracts, and find all articles, DNA, and protein sequences that mention that term.

  • Then from any article or sequence, you can move to "related articles" or "related sequences".

    • Relationships between sequences are computed with BLAST

    • Relationships between articles are computed with "MESH" terms (shared keywords)

    • Relationships between DNA and protein sequences rely on accession numbers

    • Relationships between sequences and MEDLINE articles rely on both shared keywords and the mention of accession numbers in the articles.


A search by authors: genome

“Esser” [au] AND “martin” [au]


A search by title word: genome

“Wolbachia pipientis” [ti]


Database search strategies
Database Search Strategies genome

  • General search principles - not limited to sequence (or to biology).

  • Start with broad keywords and narrow the search using more specific terms.

  • Try variants of spelling, numbers, etc.

  • Search many databases.

  • Be persistent!!


Searching pubmed
Searching PubMed genome

  • Structureless searches

    • Automatic term mapping

  • Structured searches

    • Tags, e.g. [au], [ta], [dp], [ti]

    • Boolean operators, e.g. AND, OR, NOT, ()

  • Additional features

    • Subsets, limits

    • Clipboard, history


Start working: genome

Search PubMed

cuban cigars

cuban OR cigars

“cuban cigars”

cuba* cigar*

(cuba* cigar*) NOT smok*

Fidel Castro

“fidel castro”

#6 NOT #7




The omim o nline m endelian i nheritance in m an
The genomeOMIM (Online Mendelian Inheritance in Man)

  • Genes and genetic disorders

  • Edited by team at Johns Hopkins

  • Updated daily


MIM Number Prefixes genome

* gene with known sequence

+ gene with known sequence and phenotype

# phenotype description, molecular basis known

% mendelian phenotype or locus, molecular basis unknown

no prefix other, mainly phenotypes with suspected mendelian basis


Searching omim
Searching OMIM genome

  • Search Fields

    • Name of trait, e.g., hypertension

    • Cytogenetic location, e.g., 1p31.6

    • Inheritance, e.g., autosomal dominant

    • Gene, e.g., coagulation factor VIII


OMIM search tags genome

All Fields [ALL]

Allelic Variant [AV] or [VAR]

Chromosome [CH] or [CHR]

Clinical Synopsis [CS] or [CLIN]

Gene Map [GM] or [MAP]

Gene Name [GN] or [GENE]

Reference [RE] or [REF]


Start working: genome

Search OMIM

How many types of hemophilia are there?

For how many is the affected gene known?

What are the genes involved in hemophilia A?

What are the mutations in hemophilia A?


Online Literature databases genome

1. How to use the UH online Library?

2. Online glossaries

3. Google Scholar

4. Google Books

5. Web of Science


How to use the online UH Library? genome

http://info.lib.uh.edu/


Online Glossaries genome

Bioinformatics :

http://www.geocities.com/bioinformaticsweb/glossary.html

http://big.mcw.edu/

Genomics:

http://www.geocities.com/bioinformaticsweb/genomicglossary.html

Molecular Evolution:

http://workshop.molecularevolution.org/resources/glossary/

Biology dictionary:

http://www.biology-online.org/dictionary/satellite_cells

Other glossaries, e.g., the list of phobias:

http://www.phobialist.com/class.html


4. Google Scholar genome

http://www.scholar.google.com/


What is Google Scholar? genome

Enables you to search specifically for scholarly literature, including peer-reviewed papers, theses, books, preprints, abstracts and technical reports from all broad areas of research.


Use Google Scholar to find articles from a wide variety of academic publishers, professional societies, preprint repositories and universities, as well as scholarly articles available across the web.


Google Scholar orders your search results by how relevant they are to your query, so the most useful references should appear at the top of the page

This relevance ranking takes into account the: full text of each article. the article's author, the publication in which the article appeared and how often it has been cited in scholarly literature.


What other DATA can we retrieve from the record? they are to your query, so the most


5. Google Book Search they are to your query, so the most


Start working: they are to your query, so the most

Search Google Books

How many times is the tail of the giraffe mentioned in On the Origin of Species by Mr. Darwin?


6. Web of science they are to your query, so the most

http://http://apps.webofknowledge.com.ezproxy.lib.uh.edu/WOS_GeneralSearch_input.do?product=WOS&search_mode=GeneralSearch&SID=4FB7LbbLgDMhG9fDiLh&preferencesSaved=


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