2012 03 01_bioinformatics_ii_les1

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  • The new curve saturated around 20% for alignments over more than 250 residues --- and for alignments shorter than 11 residues the new equation yielded values above 100%. However, this was acceptable as 100% identity for gragments of 10-11 residues does not imply structural similarity.
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  • SSH’s first use was as a replacement for rsh, the Unix r emote sh ell application. This tool allowed one to connect to a shell on a remote machine. The tool suffered from two major shortcomings. First, like telnet it sent all traffic in cleartext, meaning that a sniffer tool at any point between the two machines could read all commands sent and replies received. Secondly, the /etc/hosts.equiv and ~/.rhosts files listed trusted machines and users; these could make rsh connections without any further authentication. If an attacker compromised any of these trusted hosts, they would immediately get access to the rsh server with no more effort. Also, if the attacker was successfully able to spoof the IP address of a trusted host, they’d get the same access. SSH encrypts all traffic, including the password or key authentication. It also uses host keys to definitively identify both hosts involved in the communication, getting around man-in-the-middle attacks and IP spoofing.
  • The licensing issue is rather complex; depending on which release of the ssh1 and ssh2 applications you choose: Source code may or may not be available Use may be free or for cost for educational institutions Use may be free or for cost for companies The O’Reilly SSH book covers this in good detail. The SSH1 protocol has some shortcomings that aren’t easily fixed except by using the newer, but incompatible SSH2 protocol. If possible, you should use SSH clients and servers that support SSH2 and prefer it over SSH1 protocol connections.
  • The serious problem with the password approach, whether used with telnet or with ssh, is that the password you need to enter at the client end is stored on the server. Even though it’s stored in an encoded form in /etc/passwd or /etc/shadow, this password can be cracked with brute force once one has access to that file. The difference with the public/private key split is that if an attacker gets the public key stored on the server, that public key cannot be used to get back into the server! Only the private key, kept on the client only, can be used to get into a server with the public key.

Transcript

  • 1.  
  • 2. FBW 01-03-2012 Wim Van Criekinge RELOADED 2
  • 3. Inhoud
    • 09:00-11:00 (2s) (A: Theorie) Coup. Links., CL.A1057
    • 16:00-19:00 (2s) (B: Practicum) Coup. Links., CL.PC-C
    • Cursus: 40 €
    • do 16 februari: Geen Les
    • do 23 februari: Geen Les
    • do 1 maart: Recap Bioinformatics I, RDBMS, (Bio)SQL
    • do 8 maart: Web Application Developent (PHP)
    • do 15 maart: MyGenBank
    • do 22 maart: Genome Browsers
    • do 29 maart: Galaxy
    • do 5 april: Geen Les
    • do 12 april: Geen Les
    • do 19 april: Datamining (Tim De Meyer)
    • do 26 april: Textmining (Maté Ongenaert)
    • do 3 mei: Systems Biology (Bart Deplancke)
    • do 10 mei: Les 10 (projectvoorstelling)
  • 4. Les 1
    • Bioinformatics I Revisited in 5 slides
    • Why bother making databases ?
    • DataBases
      • FF
        • *.txt
        • Indexed version
      • Relational (RDBMS)
        • Access, MySQL, PostGRES, Oracle
      • OO (OODBMS)
        • AceDB, ObjectStore
      • Hierarchical
        • XML
      • Frame based system
        • Eg. DAML+OIL
      • Hybrid systems
  • 5. 4 3 2 1 0 A brief history of time (BYA) Origin of life Origin of eukaryotes insects Fungi/animal Plant/animal Earliest fossils BYA
  • 6. Rat versus mouse RBP Rat versus bacterial lipocalin
  • 7.  
  • 8. Sander-Schneider
    • HSSP: homology derived secondary structure
  • 9.  
  • 10.
    • About the Syllabus / CD
    • In tegenstelling tot Bioinformatica I is het minder de bedoeling om een overzicht te geven van de verschillende (sub)domeinen in de bioinformatica. Bioinformatica II (Reloaded) schetst een zo accuraat mogelijk beeld van de huidige stand van zaken in het bioinformatica onderzoek. Hiervoor wordt er dieper ingegaan in het gebruik van relationele databeheersystemen en hun praktische implementaties, vandaar de term “ Reloaded ”. Deze methodologie laat toe om grote heterogene datasets, typische voor biologische experimenten die meer en meer op (meta)genoomschaal worden uitgevoerd, te beheersen en gestructureerd op te slaan voor verdere (statistische) analyse. Het tweede van de cursus focust op de verschillende methodieken uit machine learning en kunstmatige intelligentie en hoe deze kunnnen ingeschakelt worden om data, via het gebruik van databanken,  om te zetten tot nieuwe verifieerbare gefundeerde hypothesis die zo hopelijk leiden tot nieuwe kennis.
  • 11.  
  • 12.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
  • 13.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • What is the protein sequence for human insulin?
    • How does the 3D structure of calmodulin look like?
    • What is the genetic location of the cystic fibrosis gene?
    • List all intron sequences in rat.
  • 14.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
  • 15.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
  • 16.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Is there any known protein sequence that is similar to x?
    • Is this gene known in any other species?
    • Has someone already cloned this sequence?
  • 17.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
  • 18.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
  • 19.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
    • Do my protein sequence contain any known motif
      • (that can give me a clue about the function)?
    • Which known sequences contain this motif?
    • Is any part of my nucleotide sequence recognized
      • by a transcriptional factor?
    • List all known start, splice and stop signals in my
      • genomic sequence.
  • 20.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
  • 21.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
    • Predictions - Using the databases as knowledge databases
  • 22.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
    • Predictions - Using the databases as knowledge databases
    • What may the structure of my protein be?
    • Secondary structure prediction.
    • Modelling by homology.
    • What is the gene structure of my genomic sequence?
    • Which parts of my protein have a high antigenicity?
  • 23.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
    • Predictions - Using the databases as knowledge databases
  • 24.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
    • Predictions - Using the databases as knowledge databases
    • Comparisons
  • 25.
    • Usage of the databases
    • Annotation searches - Search for keywords, authors, features
    • Homology (similarity) searches - Search for similar sequences
    • Pattern searches - Search for occurrences of patterns
    • Predictions - Using the databases as knowledge databases
    • Comparisons
    • Gene families
    • Phylogenetic trees
  • 26. Les 1
    • Bioinformatics I Revisited in 5 slides
    • Why bother making databases ?
    • DataBases
      • FF
        • *.txt
        • Indexed version
      • Relational (RDBMS)
        • Access, MySQL, PostGRES, Oracle
      • OO (OODBMS)
        • AceDB, ObjectStore
      • Hierarchical
        • XML
      • Frame based system
        • Eg. DAML+OIL
      • Hybrid systems
  • 27.
    • GenBank Format
    • LOCUS LISOD 756 bp DNA BCT 30-JUN-1993
    • DEFINITION L.ivanovii sod gene for superoxide dismutase.
    • ACCESSION X64011.1 GI:37619753
    • NID g44010
    • KEYWORDS sod gene; superoxide dismutase.
    • SOURCE Listeria ivanovii.
    • ORGANISM Listeria ivanovii
    • Eubacteria; Firmicutes; Low G+C gram-positive bacteria;
    • Bacillaceae; Listeria.
    • REFERENCE 1 (bases 1 to 756)
    • AUTHORS Haas,A. and Goebel,W.
    • TITLE Cloning of a superoxide dismutase gene from Listeria ivanovii
    • by functional complementation in Escherichia coli and
    • characterization of the gene product
    • JOURNAL Mol. Gen. Genet. 231 (2), 313-322 (1992)
    • MEDLINE 92140371
    • REFERENCE 2 (bases 1 to 756)
    • AUTHORS Kreft,J.
    • TITLE Direct Submission
    • JOURNAL Submitted (21-APR-1992) J. Kreft, Institut f. Mikrobiologie,
    • Universitaet Wuerzburg, Biozentrum Am Hubland, 8700
    • Wuerzburg, FRG
  • 28. FEATURES Location/Qualifiers source 1..756 /organism="Listeria ivanovii" /strain="ATCC 19119" /db_xref="taxon:1638" RBS 95..100 /gene="sod" gene 95..746 /gene="sod" CDS 109..717 /gene="sod" /EC_number="1.15.1.1" /codon_start=1 /product="superoxide dismutase" /db_xref="PID:g44011" /db_xref="SWISS-PROT:P28763" /transl_table=11 /translation="MTYELPKLPYTYDALEPNFDKETMEIHYTKHHNIYVTKL NEAVSGHAELASKPGEELVANLDSVPEEIRGAVRNHGGGHANHTLFWSSLSPN GGGAPTGNLKAAIESEFGTFDEFKEKFNAAAAARFGSGWAWLVVNNGKLEIVS TANQDSPLSEGKTPVLGLDVWEHAYYLKFQNRRPEYIDTFWNVINWDERNKRF DAAK" terminator 723..746 /gene="sod"
  • 29.
    • Example of location descriptors
    • Location Description
    • 476 Points to a single base in the presented sequence
    • 340..565 Points to a continuous range of bases bounded by and
    • including the starting and ending bases
    • <345..500 The exact lower boundary point of a feature is unknown.
    • (102.110) Indicates that the exact location is unknown but that it
    • is one of the bases between bases 102 and 110.
    • (23.45)..600 Specifies that the starting point is one of the bases
    • between bases 23 and 45, inclusive, and the end base 600
    • 123^124 Points to a site between bases 123 and 124
    • 145^177 Points to a site anywhere between bases 145 and 177
    • J00193:hladr Points to a feature whose location is described in
    • another entry: the feature labeled 'hladr' in the
    • entry (in this database) with primary accession 'J00193'
  • 30. BASE COUNT 247 a 136 c 151 g 222 t ORIGIN 1 cgttatttaa ggtgttacat agttctatgg aaatagggtc tatacctttc gccttacaat 61 gtaatttctt ttcacataaa taataaacaa tccgaggagg aatttttaat gacttacgaa 121 ttaccaaaat taccttatac ttatgatgct ttggagccga attttgataa agaaacaatg 181 gaaattcact atacaaagca ccacaatatt tatgtaacaa aactaaatga agcagtctca 241 ggacacgcag aacttgcaag taaacctggg gaagaattag ttgctaatct agatagcgtt 301 cctgaagaaa ttcgtggcgc agtacgtaac cacggtggtg gacatgctaa ccatacttta 361 ttctggtcta gtcttagccc aaatggtggt ggtgctccaa ctggtaactt aaaagcagca 421 atcgaaagcg aattcggcac atttgatgaa ttcaaagaaa aattcaatgc ggcagctgcg 481 gctcgttttg gttcaggatg ggcatggcta gtagtgaaca atggtaaact agaaattgtt 541 tccactgcta accaagattc tccacttagc gaaggtaaaa ctccagttct tggcttagat 601 gtttgggaac atgcttatta tcttaaattc caaaaccgtc gtcctgaata cattgacaca 661 ttttggaatg taattaactg ggatgaacga aataaacgct ttgacgcagc aaaataatta 721 tcgaaaggct cacttaggtg ggtcttttta tttcta //
  • 31.
    • EMBL format
    • ID LISOD standard; DNA; PRO; 756 BP. IDentification
    • XX
    • AC X64011; S78972; Accession (Axxxxx, Afxxxxxx), GUID
    • XX
    • NI g44010 Nucleotide Identifier --> x.x
    • XX
    • DT 28-APR-1992 (Rel. 31, Created) DaTe
    • DT 30-JUN-1993 (Rel. 36, Last updated, Version 6)
    • XX
    • DE L.ivanovii sod gene for superoxide dismutase DEscription
    • XX.
    • KW sod gene; superoxide dismutase. KeyWord
    • XX
    • OS Listeria ivanovii Organism Species
    • OC Eubacteria; Firmicutes; Low G+C gram-positive bacteria; Bacillaceae;
    • OC Listeria. Organism Classification
    • XX
    • RN [1]
    • RA Haas A., Goebel W.; Reference
    • RT &quot;Cloning of a superoxide dismutase gene from Listeria ivanovii by
    • RT functional complementation in Escherichia coli and
    • RT characterization of the gene product.&quot;;
    • RL Mol. Gen. Genet. 231:313-322(1992).
    • XX
  • 32.
    • Example of a SwissProt entry
    • ID TNFA_HUMAN STANDARD; PRT; 233 AA. IDentification
    • AC P01375; ACcession
    • DT 21-JUL-1986 (REL. 01, CREATED) DaTe
    • DT 21-JUL-1986 (REL. 01, LAST SEQUENCE UPDATE)
    • DT 15-JUL-1998 (REL. 36, LAST ANNOTATION UPDATE)
    • DE TUMOR NECROSIS FACTOR PRECURSOR (TNF-ALPHA) (CACHECTIN).
    • GN TNFA. Gene name
    • OS HOMO SAPIENS (HUMAN). Organism Species
    • OC EUKARYOTA; METAZOA; CHORDATA; VERTEBRATA; TETRAPODA; MAMMALIA;
    • OC EUTHERIA; PRIMATES. Organism Classification
    • RN [1] Reference
    • RP SEQUENCE FROM N.A.
    • RX MEDLINE; 87217060.
    • RA NEDOSPASOV S.A., SHAKHOV A.N., TURETSKAYA R.L., METT V.A.,
    • RA AZIZOV M.M., GEORGIEV G.P., KOROBKO V.G., DOBRYNIN V.N.,
    • RA FILIPPOV S.A., BYSTROV N.S., BOLDYREVA E.F., CHUVPILO S.A.,
    • RA CHUMAKOV A.M., SHINGAROVA L.N., OVCHINNIKOV Y.A.;
    • RL COLD SPRING HARB. SYMP. QUANT. BIOL. 51:611-624(1986).
    • RN [2]
    • RP SEQUENCE FROM N.A.
    • RX MEDLINE; 85086244.
    • RA PENNICA D., NEDWIN G.E., HAYFLICK J.S., SEEBURG P.H., DERYNCK R.,
    • RA PALLADINO M.A., KOHR W.J., AGGARWAL B.B., GOEDDEL D.V.;
    • RL NATURE 312:724-729(1984).
    • ...
  • 33. CC -!- FUNCTION: CYTOKINE WITH A WIDE VARIETY OF FUNCTIONS: IT CAN CC CAUSE CYTOLYSIS OF CERTAIN TUMOR CELL LINES, IT IS IMPLICATED CC IN THE INDUCTION OF CACHEXIA, IT IS A POTENT PYROGEN CAUSING CC FEVER BY DIRECT ACTION OR BY STIMULATION OF IL-1 SECRETION, IT CC CAN STIMULATE CELL PROLIFERATION & INDUCE CELL DIFFERENTIATION CC UNDER CERTAIN CONDITIONS. Comments CC -!- SUBUNIT: HOMOTRIMER. CC -!- SUBCELLULAR LOCATION: TYPE II MEMBRANE PROTEIN. ALSO EXISTS AS CC AN EXTRACELLULAR SOLUBLE FORM. CC -!- PTM: THE SOLUBLE FORM DERIVES FROM THE MEMBRANE FORM BY CC PROTEOLYTIC PROCESSING. CC -!- DISEASE: CACHEXIA ACCOMPANIES A VARIETY OF DISEASES, INCLUDING CC CANCER AND INFECTION, AND IS CHARACTERIZED BY GENERAL ILL CC HEALTH AND MALNUTRITION. CC -!- SIMILARITY: BELONGS TO THE TUMOR NECROSIS FACTOR FAMILY. DR EMBL; X02910; G37210; -. Database Cross-references DR EMBL; M16441; G339741; -. DR EMBL; X01394; G37220; -. DR EMBL; M10988; G339738; -. DR EMBL; M26331; G339764; -. DR EMBL; Z15026; G37212; -. DR PIR; B23784; QWHUN. DR PIR; A44189; A44189. DR PDB; 1TNF; 15-JAN-91. DR PDB; 2TUN; 31-JAN-94.
  • 34. KW CYTOKINE; CYTOTOXIN; TRANSMEMBRANE; GLYCOPROTEIN; SIGNAL-ANCHOR; KW MYRISTYLATION; 3D-STRUCTURE. KeyWord FT PROPEP 1 76 Feature Table FT CHAIN 77 233 TUMOR NECROSIS FACTOR. FT TRANSMEM 36 56 SIGNAL-ANCHOR (TYPE-II PROTEIN). FT LIPID 19 19 MYRISTATE. FT LIPID 20 20 MYRISTATE. FT DISULFID 145 177 FT MUTAGEN 105 105 L->S: LOW ACTIVITY. FT MUTAGEN 108 108 R->W: BIOLOGICALLY INACTIVE. FT MUTAGEN 112 112 L->F: BIOLOGICALLY INACTIVE. FT MUTAGEN 162 162 S->F: BIOLOGICALLY INACTIVE. FT MUTAGEN 167 167 V->A,D: BIOLOGICALLY INACTIVE. FT MUTAGEN 222 222 E->K: BIOLOGICALLY INACTIVE. FT CONFLICT 63 63 F -> S (IN REF. 5). FT STRAND 89 93 FT TURN 99 100 FT TURN 109 110 FT STRAND 112 113 FT TURN 115 116 FT STRAND 118 119 FT STRAND 124 125
  • 35. FT STRAND 130 143 FT STRAND 152 159 FT STRAND 166 170 FT STRAND 173 174 FT TURN 183 184 FT STRAND 189 202 FT TURN 204 205 FT STRAND 207 212 FT HELIX 215 217 FT STRAND 218 218 FT STRAND 227 232 SQ SEQUENCE 233 AA; 25644 MW; 666D7069 CRC32; MSTESMIRDV ELAEEALPKK TGGPQGSRRC LFLSLFSFLI VAGATTLFCL LHFGVIGPQR EEFPRDLSLI SPLAQAVRSS SRTPSDKPVA HVVANPQAEG QLQWLNRRAN ALLANGVELR DNQLVVPSEG LYLIYSQVLF KGQGCPSTHV LLTHTISRIA VSYQTKVNLL SAIKSPCQRE TPEGAEAKPW YEPIYLGGVF QLEKGDRLSA EINRPDYLDF AESGQVYFGI IAL //
  • 36.
    • Structure databases
    • Protein Data Bank (PDB)
    • Protein Data Bank - http://www.rcsb.org/pdb
    • Diffraction 7373 structures determined by X-ray diffraction
    • NMR 388 structures determined by NMR spectroscopy
    • Theoretical Model 201 structures proposed by modeling
  • 37. PDB
  • 38. PDB
  • 39. PDB
  • 40. PDB
  • 41. Visualizing Structures Cn3D versie 4.0 (NCBI)
  • 42. Les 1
    • Bioinformatics I Revisited in 5 slides
    • Why bother making databases ?
    • DataBases
      • FF
        • *.txt
        • Indexed version
      • Relational (RDBMS)
        • Access, MySQL, PostGRES, Oracle
      • OO (OODBMS)
        • AceDB, ObjectStore
      • Hierarchical
        • XML
      • Frame based system
        • Eg. DAML+OIL
      • Hybrid systems
  • 43. Problems with Flat files …
    • Wasted storage space
    • Wasted processing time
    • Data control problems
    • Problems caused by changes to data structures
    • Access to data difficult
    • Data out of date
    • Constraints are system based
    • Limited querying eg. all single exon GPCRs (<1000 bp)
  • 44.
    • What is a relational database ?
      • Sets of tables and links (the data)
      • A language to query the datanase (Structured Query Language)
      • A program to manage the data (RDBMS)
    • Flat files are not relational
      • Data type (attribute) is part of the data
      • Record order mateters
      • Multiline records
      • Massive duplication
        • Bv Organism: Homo sapeinsm Eukaryota, …
      • Some records are hierarchical
        • Xrefs
      • Records contain multiple “sub-records”
      • Implecit “Key”
  • 45.
    • records
    • fields
    • linear file of homogeneous records
    name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address...................... name......................... surname.................... phone........................ address......................
  • 46.
    • Terms and concepts:
      • tuple
      • domain
      • attribute
      • key
      • integrity rules
  • 47. Introduction to Database Systems
    • Historic Background
      • Hierarchical databases (IMS) - IBM 1968
        • Hierarchical structures between file records
      • Network databases - CODASYL Group 1969
        • Network structures of record types
        • Linked chains between 'Owner' and 'Member' records
        • Included in Cobol, procedural language - Manual navigation
      • Relational Data Model - E. F. Codd 1970
        • Mathematical foundation of databases
        • New non-procedural language SQL - Automatic navigation
      • Object-relational databases
      • Object-oriented databases
  • 48. Relational
    • The Relational model is not only very mature , but it has developed a strong knowledge on how to make a relational back-end fast and reliable, and how to exploit different technologies such as massive SMP, Optical jukeboxes, clustering and etc. Object databases are nowhere near to this, and I do not expect then to get there in the short or medium term.
    • Relational Databases have a very well-known and proven underlying mathematical theory, a simple one (the set theory) that makes possible
      • automatic cost-based query optimization,
      • schema generation from high-level models and
      • many other features that are now vital for mission-critical Information Systems development and operations.
  • 49. The Benefits of Databases
    • Redundancy can be reduced
    • Inconsistency can be avoid ed
    • Conflicting requirements can be balanced
    • Standards can be enforced
    • Data can be shared
    • Data independence
    • Integrity can be maintained
    • Security restrictions can be applied
  • 50. Relational Terminology ID NAME PHONE EMP_ID 201 Unisports 55-2066101 12 202 Simms Atheletics 81-20101 14 203 Delhi Sports 91-10351 14 204 Womansport 1-206-104-0103 11 Row (Tuple) Column (Attribute) CUSTOMER Table (Relation)
  • 51. Relational Database Terminology
    • Each row of data in a table is uniquely identified by a primary key (PK)
    • Information in multiple tables can be logically related by foreign keys (FK)
    ID LAST_NAME FIRST_NAME 10 Havel Marta 11 Magee Colin 12 Giljum Henry 14 Nguyen Mai ID NAME PHONE EMP_ID 201 Unisports 55-2066101 12 202 Simms Atheletics 81-20101 14 203 Delhi Sports 91-10351 14 204 Womansport 1-206-104-0103 11 Table Name: CUSTOMER Table Name: EMP Primary Key Foreign Key Primary Key
  • 52. Relational Database Terminology Relational operators
    • Relational
      • select
        • rel WHERE boolean-xpr
      • project
        • rel [ attr-specs ]
      • join
        • rel JOIN rel
      • divide by
        • rel DIVIDEBY rel
    • Set-based
        • rel UNION rel
        • rel INTERSECT rel
        • rel MINUS rel
        • rel TIMES rel
  • 53. Disadvantages
    • size
    • complexity
    • cost
    • Additional hardware costs
    • Higher impact of failure
    • Recovery more difficult
  • 54.
    • RDBM products
      • Free
        • MySQL, very fast, widely usedm easy to jump into but limited non standard SQL
        • PostrgreSQL – full SQLm limited OO, higher learning curve than MySQL
      • Commercial
        • MS Access – Great query builder, GUI interfaces
        • MS SQL Server – full SQL, NT only
        • Oracle, everything, including the kitchen sink
        • IBM DB2, Sybase
  • 55. Example 3-tier model in biological database http://www.bioinformatics.be Example of different interface to the same back-end database (MySQL)
  • 56. What is the Internet?
    • A network of networks
    • Based on TCP/IP (Transmission Control Protocol/Internet Protocol)
    • Global
    • A variety of services and tools
  • 57. What is the World Wide Web?
    • The Web presents information as a series of &quot;documents,&quot; often referred to as web pages, that are prepared using the Hypertext Markup Language (HTML).
    • Using HTML, the document's author can specially code sections of the document to &quot;point&quot; to other information resources. These specially coded sections are referred to as hypertext links.
    • Users viewing the webpage can select the hypertext link and retrieve or connect to the information resource that the link points to.
  • 58. What is HTTP? In Summary : HTTP is an acronym for Hypertext Transfer Protocol. HTTP is the set of rules, or protocol, that enables hypertext data to be transferred from one computer to another, and is based on the client/server principle. Hypertext is text that is coded using the Hypertext Markup Language. These codes and HTTP work together to link resources to each other. HTTP enables users to retrieve a wide variety of resources such as text, graphics, sound, animation and other hypertext documents, and allows hypertext access to other Internet protocols.
  • 59. What is HTML?
    • Standardized codes
    • Web pages
    • SGML
    • Descriptive markup
    • Tags
  • 60. What is HTML? HTML stands for Hypertext Markup Language. HTML consists of standardized codes, or &quot;tags&quot;, that are used to define the structure of information on a web page. HTML is used to prepare documents for the World Wide Web. A web page is single a unit of information, often called a document, that is available on the World Wide Web. HTML defines several aspects of a web page including heading levels, bold, italics, images, paragraph breaks and hypertext links to other resources.
  • 61. What is HTML? HTML is a sub-language of SGML, or Standard Generalized Markup Language. SGML is a system that defines and standardizes the structure of documents. Both SGML and HTML utilize descriptive markup to define the structure of an area of text. In general terms, descriptive markup does not specify a particular font or point size for an area of text. Instead, it describes an area of text as a heading or a caption, for example. Therefore, in HTML, text is marked as a heading, subheading, numbered list, bold, italic, etc.
  • 62. What is a URL? URLs consist of letters, numbers, and punctuation. The basic structure of a URL is hierarchical, and the hierarchy moves from left to right: Examples: http://www.healthyway.com:8080/exercise/mtbike.html gopher://gopher.state.edu/ ftp://ftp.company.com/ protocol://server-name.domain-name.top-level domain:port/directory/filename
  • 63. What is an IP Address?
    • A way to identify machines on the Internet
    • A number
    • Unique
    • Global
    • Standardized
  • 64. What is an IP Address? If you want to connect to another computer, transfer files to or from another computer, or send an e-mail message, you first need to know where the other computer is - you need the computer's &quot;address.&quot; An IP (Internet Protocol) address is an identifier for a particular machine on a particular network; it is part of a scheme to identify computers on the Internet. IP addresses are also referred to as IP numbers and Internet addresses. An IP address consists of four sections separated by periods. Each section contains a number ranging from 0 to 255. Example = 198.41.0.52
  • 65. What is an IP Address? The diagram below compares Class A, Class B and Class C IP addresses. The blue numbers represent the network and the red numbers represent hosts on the network. Therefore, a Class A network can support many more hosts than a Class C network.
  • 66. What is Internet Addressing? Most computers on the Internet have a unique domain name. Special computers, called domain name servers, look up the domain name and match it to the corresponding IP address so that data can be properly routed to its destination on the Internet. An example domain name is: healthyway.com Domain names are easier for most people to relate to than a numeric IP address.
  • 67. What is Internet Addressing?
    • URL stands for Uniform Resource Locator. URLs are used to identify specific sites and files available on the World Wide Web.
    • The structure of a URL is:
    • protocol://server.subdomain.top-level-domain/directory/filename
    • Not all URLs will have the directory and filename.
    • Two examples:
    • http://www.healthyway.com/exercise/mtbike.html
    • gopher://gopher.state.edu/
  • 68. What is TCP/IP?
    • A suite of protocols
    • Rules for sending and receiving data across
    • Networks
    • Addressing
    • Management and verification
  • 69. What is TCP/IP? TCP/IP stands for Transmission Control Protocol/Internet Protocol. TCP/IP is actually a collection of protocols, or rules, that govern the way data travels from one machine to another across networks. The Internet is based on TCP/IP.
  • 70. What is TCP/IP?
    • TCP/IP has two major components: TCP and IP.
    • IP:
    • envelopes and addresses the data
    • enables the network to read the envelope and forward the data to its destination
    • defines how much data can fit in a single &quot;envelope&quot; (a packet)
  • 71. What is TCP/IP? The relationship between data, IP, and networks is often compared to the relationship between a letter, its addressed envelope, and the postal system.
  • 72. What is TCP/IP?
    • TCP:
    • breaks data up into packets that the network can handle efficiently
    • verifies that all the packets arrive at their destination
    • &quot;reassembles&quot; the data
    • TCP/IP can be compared to moving across country.
  • 73. What is a packet?
    • Unit of information
    • Data
    • Header Information
    • Routers
    • TCP/IP
  • 74. What is a packet?
    • A packet is a single unit, or &quot;package&quot;, of data that is sent across a network. Data is broken into packets before it is sent across the Internet. Types of data that are sent across the Internet using packets include:
      • E-mail messages
      • Files, via File Transfer Protocol (FTP)
      • Web pages, via the World Wide Web (WWW)
  • 75. What is a packet? In addition to the actual data, packets also contain header information. The header of a packet contains both the originating and destination IP (Internet Protocol) address. The header also contains coding to handle transmission errors and keep packets flowing. Header information can be compared to addressing an envelope. Like the header of a packet, an envelope contains the addresses of both the sender and the recipient, in order to keep track of who the envelope is from and who it is going to.
  • 76. What is a packet? Header information is used by routers to send packets across a network. Routers are computers that are dedicated to &quot;reading&quot; header information and determining which router to send the packet to next. Packets move from router to router until they reach their final destination, in much the same way that an envelope travels between postal substations before reaching the recipient. The packets that make up data, such as an e-mail message or a web page, will not necessarily all follow the same route to the final destination. The route that a packet travels depends on many variables, including network traffic at that particular moment and the size of the packet being sent.
  • 77. What is a packet? Transmission Control Protocol/Internet Protocol (TCP/IP) is a set of rules that govern how data is transmitted across networks and the Internet. TCP/IP utilizes packets to send information across the Internet. TCP and IP have different functions related to packets.
  • 78. What is a packet?
    • TCP completes the following:
      • Sends the packets in sequence, so they arrive at their destination in the correct order.
      • Ensures the integrity of packets. If a packet has been damaged, TCP will request that the damaged packet be resent.
  • 79. What is a packet?
    • IP completes the following:
      • Breaks the data into packets.
      • Places header information into the packet, enabling the packet to be forwarded from router to router until it reaches the final destination.
      • Determines how much data can fit into a single packet.
  • 80. What is a packet? The following diagram illustrates an e-mail message being sent across a network. 1. Data that makes up an e-mail message is split into packets by the IP portion of TCP/IP. IP also adds header information to each packet. 2. Using header information in the packets, routers determine the best path for each packet to take to its final destination. 3. The TCP portion of TCP/IP reassembles the packets in the correct order and ensures that all packets have arrived undamaged. Message is sent
  • 81. What is Telnet? Telnet is a protocol, or set of rules, that enables one computer to connect to another computer. This process is also referred to as remote login. The user's computer, which initiates the connection, is referred to as the local computer, and the machine being connected to, which accepts the connection, is referred to as the remote, or host, computer. The remote computer can be physically located in the next room, the next town, or in another country.
  • 82. What is Telnet? Once connected, the user's computer emulates the remote computer. When the user types in commands, they are executed on the remote computer. The user's monitor displays what is taking place on the remote computer during the telnet session. The procedure for connecting to a remote computer will depend on how your Internet access is set-up.
  • 83. What is Telnet? Once a connection to a remote computer is made, instructions or menus may appear. Some remote machines may require a user to have an account on the machine, and may prompt users for a username and password. Many resources, such as library catalogs, are available via telnet without an account and password. Here is an example taken from a telnet session to Washington University in St. Louis, MO:
  • 84. SSH Features
    • Command line terminal connection tool
    • Replacement for rsh, rcp, telnet, and others
    • All traffic encrypted
    • Both ends authenticate themselves to the other end
    • Ability to carry and encrypt non-terminal traffic
  • 85. Brief History
    • SSH.com’s SSH1, originally completely free with source code, then license changed with version 1.2.13
    • SSH.com’s SSH2, originally only commercial, but now free for some uses.
    • OpenSSH team took the last free SSH1 release, refixed bugs, added features, and added support for the SSH2 protocol.
  • 86. SSH key background
    • Old way: password stored on server, user supplied password compared to stored version
    • New way: private key kept on client, public key stored on server.
  • 87. What is FTP?
    • Protocol
    • File transfer
    • Client/Server based
    • Anonymous FTP
    • File types
    • Compression
  • 88. What is FTP?
    • FTP stands for File Transfer Protocol, and is part of the TCP/IP protocol suite. It is the protocol, or set of rules, which enables files to be transferred between computers.
    • FTP is a powerful tool which allows files to be transferred from “computer A” to “computer B”, or vice versa.
  • 89. What is FTP?
    • FTP works on the client/server principle. A client program enables the user to interact with a server in order to access information and services on the server computer.
    • Files that can be transferred are stored on special computers called FTP servers. To access these files, an FTP client program is used. This is an interface that allows the user to locate the file(s) to be transferred and initiate the transfer process.
  • 90. What is FTP?
    • The basic steps to use FTP are:
    • Connect to the FTP server
    • Navigate the file structure to find the file you want
    • Transfer the file
    • The specifics of each step will vary, depending on the client program being used and the type of Internet connection.
  • 91. What is FTP? Anonymous FTP Anonymous FTP allows a user to access a wealth of publicly available information. No special account or password is needed. However, an anonymous FTP site will sometimes ask that users login with the name “anonymous” and use their e-mail address as the password.
  • 92. What is FTP?
    • There is a wide variety of files that are publicly available through anonymous FTP:
    • Shareware - software that you can use free for a trial period but then pay a fee for
    • Freeware - completely free software, for example fonts, clipart and games
    • Upgrades & Patches - upgrades to current software and “fixes” for software problems
    • Documents - examples include research papers, articles and Internet documentation
  • 93. What is FTP? Files on FTP servers are often compressed. Compression decreases file size. This enables more files to be stored on the server and makes file transfer times shorter. In order to use a compressed file it needs to be decompressed using appropriate software. It is a good idea to have current virus checking software on the computer before files are downloaded to it.
  • 94.  
  • 95.  
  • 96.  
  • 97.  
  • 98. BioSQL
  • 99. Conclusions
    • A database is a central component of any contemporary information system
    • The operations on the database and the mainenance of database consistency is handled by a DBMS
    • There exist stand alone query languages or embedded languages but both deal with definition (DDL) and manipulation (DML) aspects
    • The structural properties, constraints and operations permitted within a DBMS are defined by a data model - hierarchical, network, relational
    • Recovery and concurrency control are essential
    • Linking of heterogebous datasources is central theme in modern bioinformatics