Effective design and analysis of bioinformation Unit 3

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Effective design and analysis of
bioinformationUnit 3

• BIOL221T Advanced Bioinformatics for
  Biotechnology

Irene Gabashvili, PhD igabashvili_at_yahoo.com
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Course availability

• Lectures Lab every Wednesday, Duncan Hall,
  Room 550, 600 pm to  945 pm
• Office hours Wednesday, 4pm-6pm (Room 554,
  phone [phone]) and by appointment
• Lecture notes will be posted at
  http//home.comcast.net/igabashvili/221T.htm
• Or the SJSU page --
• The user name is ewok\biostudents (dont enter
  quotation mark)  
• And the password is 4biolecture (dont enter
  quotation mark).

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Consumer genomics gets crowded
In the News

• http//www.seqwright.com/ SoliD, ABI
• http//www.decodeme.com/ Illumina
• https//www.23andme.com/ Illumina
• http//www.navigenics.com/ Affymetrix
• http//www.knome.com/ ABI,Amersham,Illumina

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https//www.23andme.com/experts/letters/science/
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List from DeCODE genetics

• Our current list of diseases includes
  Age-related Macular Degeneration, Asthma,
  Alzheimer's Disease, Atrial Fibrillation, Breast
  Cancer, Celiac Disease, Colorectal Cancer,
  Exfoliation Glaucoma XFG, Crohn's Disease,
  Multiple Sclerosis, Myocardial Infarction,
  Obesity, Prostate Cancer, Psoriasis, Restless
  Legs, Rheumatoid Arthritis, Type 1 Diabetes and
  Type 2 Diabetes.

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Three important sub-disciplines within
bioinformatics

• the development of new algorithms and statistics
  with which to assess relationships among members
  of large data sets
• the analysis and interpretation of various types
  of data including nucleotide and amino acid
  sequences, protein domains, and protein
  structures
• the development and implementation of tools that
  enable efficient access and management of
  different types of biological information.

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biomedical informatics
Main tasks of

• Storage, Analysis, Visualization and Management
  of biomedical data
• Mining for new knowledge, hypothesis formulation
  and testing
• Development of tools and resources for the above

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Brief History of Bioinformatics

• 1920 - term genome was introduced by H. Winkler
  to denote the complete set of chromosomal and
  extra chromosomal genes
• 1933 - A new technique, electrophoresis, is
  introduced by Tiselius for separating proteins in
  solution.
• 1951 - Pauling and Corey propose the structure
  for the alpha-helix and beta-sheet

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Brief History of Bioinformatics

• 1953 - Watson Crick propose the double helix
  model for DNA (data by Franklin Wilkins)
• 1954 - Perutz's group develop methods to solve
  the phase problem in protein crystallography.
• 1955 - The sequence of the first protein to be
  analyzed, bovine insulin, announced by F.Sanger.
• 1956 - The first protein sequence reported was
  that of bovine insulin, consisting of 51 residues

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Brief History of Bioinformatics

• 1962 - Pauling's theory of molecular evolution
• 1965 M.Dayhoffs Atlas of Protein Sequences
• 1970 - Needleman-Wunsch algorithm
• 1972 The Protein DataBank
• 1980 - The first complete gene sequence for an
  organism (FX174)5,386 bp, nine proteins.
• 1981 - The Smith-Waterman algorithm IBM
  introduces its PC to the market. The concept of
  a sequence motif ( Doolittle )

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Brief History of Bioinformatics

• 1983 Sequence DB searching (Wilbur-Lipman)
• 1986 - Human Genome Initiative announcement
• 1987 SWISSPROT protein sequence database
• 1988 - NCBI created at NIH/NLM (databases)
• 1988 - FASTA by Pearson and Lupman EMBL
  establish sequence database network
• 1990 - BLAST by Altschul,et.al.
• 2003 -Human Genome Project Completion

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biomedical informatics
The data of

• Public Private Databases store biological data
  in various formats
• Sequences DNA, RNA, proteins
• Structures X-ray, NMR, microscopy
• Expression microarrays, gels
• Interaction 2 hybrid, mass spec
• Metabolism GC-MS, NMR
• Physiology medical images, PK/PD

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Search Engines

• AND, OR, NOT
• Specifying database fields (Organism, Author)
• Order of words, neonatal pre/3 screening
  (neonatal at least 3 words before screening
• Spaces wom?n cats

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Search Download

• Entrez integrated, text-based search and
  retrieval system for PubMed, Nucleotide and
  Protein Sequences, Protein Structures, Complete
  Genomes, Taxonomy, etc batch download
• http//www.ncbi.nlm.nih.gov/sites/batchentrez
• term field OPERATOR term field
• 110ESTC AND Homo sapiensORGN AND
  deafnessdis (BSND Bartter syndrome,
  infantile, with sensorineural deafness)
• http//www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD
  searchDBunigene
• More on the courses website

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DATA FORMATS AND DATA INTEGRATION

• It is widely recognized that successful data
  integration is one of the keys to improved
  productivity in biopharmaceutical RD
• Success in most bioinformatics-related
  activities, from functional characterization of
  genomic sequences to prioritization of drug
  targets, requires an integrated view of all
  relevant data in a drug discovery RD program
• Bioinformatics data sources often have large,
  complex data structures, reflecting the richness
  of the scientific concepts they model. Many
  bioinformatics data sources cover similar
  domains, such as genes, proteins, sequence
  annotations or microarray results.

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Database design links

•  http//www.devx.com/ibm/Article/20702
•  http//www.campus.ncl.ac.uk/databases/design/
• http//www.dbazine.com/mullins_datamodel.shtml
• http//www.extropia.com/tutorials/sql/toc.html
• http//www.surfermall.com/relational/lesson_1.htm
  

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Database Definition

• A collection of data that
• is organized
• usually computer-based
• represents repetitive information implicitly
• supports retrieval
• A set of rules to manipulate data
• A method to mold information into knowledge

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Database applications

• Who uses Computerized Databases
• Stores to keep track of inventory
• Hospitals to track of patient info
• Travel agents to keep up with their customers
  and reservations
• Biologists to efficiently manage and manipulate
  their data
• DATA ? INFORMATION ? KNOWLEDGE

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Paper Database as Expert System
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HISTORY

• 1960's Two main data models are developed
  network model (CODASYL) and hierarchical (IMS). A
  user would need to know the physical structure of
  the database in order to query for information.
  SABRE IBM/AA.
• 1970-72 E.F. Codd proposed relational model He
  disconnects the schema (logical organization) of
  a database from the physical storage methods.

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HISTORY

• 1970's
• Ingres UCB ? Ingres Corp., Sybase, MS SQL
  Server, Britton-Lee, Wang's PACE. This system
  used QUEL as query language.
• System R IBM ? IBM's SQL/DS DB2, Oracle, HP's
  Allbase, Tandem's Non-Stop SQL. This system used
  SEQUEL as query language.
• The term Relational Database Management System
  (RDBMS) is coined

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HISTORY

• 1976 P. Chen proposed the Entity-Relationship
  (ER) model for database design
• Early 1980's Commercialization of relational
  systems begins as a boom
• Mid-1980's SQL (Structured Query Language)
  becomes "intergalactic standard". DB2 becomes
  IBM's flagship product. Network and hierarchical
  models fade into the background

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HISTORY

• Early 1990's Application and personal
  productivity tool development PowerBuilder
  (Sybase), Oracle Developer, VB (Microsoft),
  Excel/Access (MS) and ODBC. First Object Database
  Management Systems (ODBMS) prototypes.
• Mid-1990's Internet/WWW. Web/DB grows
  exponentially, usable for average users

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HISTORY

• Late-1990's Boom for Web/Internet/DB connectors.
  Open source solution with widespread use of gcc,
  cgi, Apache, MySQL, etc. Online Transaction
  processing (OLTP) and online analytic processing
  (OLAP) comes of age
• Early 21st century Burst of.com but solid growth
  of DB applications. PDAs, POS transactions, IBM,
  Microsoft, Oracle.

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FUTURE

• Terabyte and Petabyte databases of everything
• Mobile databases
• Semantic Web
• Object Oriented Everything, includes databases
• Object Database Management Group (ODMG) standards
  are proposed and accepted
• Security issues

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Database advantages

• An advantage of a database program is
• Can find a specific file quickly
• Can easily add records
• Can alphabetize and sort data faster than most
  people
• Is as accurate as the data that is entered
• Can make many different types of reports
• Is invaluable for large amounts of data

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Database Parts

• Parts of a relational database
• Fields-categories of information
• lttablegt
• Entry data in a field
• Record all of the information about one item
  (row)
• File document of all of the records
• To sort field, ascend or descend (Excel, Works)

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Database types

• Flat (spreadsheet)
• Hierarchical
• Network (two fundamental constructs, called
  records and sets)
• Relational

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Relational Databases

• Relational databases started to get to be a big
  deal in the 1970's, and they're still a big deal
  today, which is a little peculiar, because
  they're a 1960's technology.
• A relational database is a bunch of rectangular
  tables. Each row of a table is a record about one
  person or thing the record contains several
  pieces of information called fields.

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Entities and Relationships
Entities things we store information
about Relationships links between the
entities Many-to-many One-to-one One-to-many
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A Table is a Relation
Columns, Fields, Attributes Rows, Records,
Tuples, Entities. records of data, comprised of
fields, stored in tables
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Keys and Functional Dependencies

• Key field (superkey, key) - a field that uniquely
  identifies a record
• If there is a functional dependency between
  column A and column B in a given table,
• (A ? B), then the value of column A determines
  the value of column B. (employeeID ? name)

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Schema

• Database schema is the structure or design of the
  database, a blueprint for the data in the
  database.
• employee(employeeID, name, job, cube,
  departmentID)
• What information needs to be stored? (things or
  entities)
• What questions will we ask of the database?
  (queries.)

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Flawed schemas
This Schema design leads to redundancies Employee(
employee ID, name, job, department
ID Department(Department ID, Department name)
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Flawed schemas
Insertion Anomaly
Deletion Anomaly
Update Anomaly
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Avoid Null Values
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Normalization
Unnormlized table lists instead of atomic
numbers. This violates the rules of first normal
form
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Normalization
This schema is in first normal form, 1NF
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Second Normal Form, 2NF
2NF Attributes must depend on the whole key
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3NF and BCNF (Boyce-Codd)
3NF Attributes must depend on nothing but the
key BCNF all the functional dependencies must
have a superkey on the left side
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Concepts

• Entities are things, and relationships are the
  links between them.
• Relations or tables hold a set of data in tabular
  form.
• Columns belonging to tables describe the
  attributes that each data item possesses.
• Rows in tables hold data items with values for
  each column in a table.
• Keys are used to identify a single row.
• Functional dependencies identify which attributes
  determine the values of other attributes.
• Schemas are the blueprints for a database.

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Design Principles

• Minimize redundancy without losing data.
• Insertion, deletion, and update anomalies are
  problems that occur when trying to insert,
  delete, or update data in a table with a flawed
  structure.
• Avoid designs that will lead to large quantities
  of null values.

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Normalization

• Normalization is a formal process for improving
  database design.
• First normal form (1NF) means atomic column or
  attribute values.
• Second normal form (2NF) means that all
  attributes outside the key must depend on the
  whole key.
• Third normal form (3NF) means no transitive
  dependencies.
• Boyce-Codd normal form (BCNF) means that all
  attributes must be functionally determined by a
  superkey.

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Hierarchical Databases
1234567
Sandiego, Carmen
123 Main Street
Labs
Chem7
Chem7
K 3.9
Na142
K 4.3
Na136
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Hierarchical Databases

• Easy to use
• Efficient storage
• Tree walking is fast
• Queries across trees are slow
• Flexible
• Too flexible chaos is allowed
• Too easy to modify
• Difficult to document complex structures

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Hierarchical Databases

• EMR(1234567)Sandiego, Carmen
• EMR(1234567, Address)123 Main Street
• EMR(1234567, Chem7, 2/2/02, Na)136
• EMR(1234567, Chem7, 2/2/02, K)4.3
• EMR(1234567, Chem7, 2/3/02, Na)142
• EMR(1234567, Chem7, 2/3/02, K)3.9

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Hierarchical Chaos
1234567
Admissions
Admission 1
Admit Date 2/2/02
Primary DX CHF
Other DX
AODM
A Fib
Flag S
Flag P
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Network Databases
1234567
Gyn Clinic
2 Main St.
Sandiego
305-2500
Secretary
Gyn Clinic
8AM-5PM
Ms Smith
305-1000
Service
Pap
Dr. Jones
Gyn Visit
Beeper 34
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Extensible Markup Language (XML) Databases

• SGML is a metalanguage
• SGML is used to write Document Type Definitions
  (DTDs) that define languages
• HTML is a language with an SGML DTD
• Tags are for formatting/presentation syntax
• XML is a proper subset of SGML
• XML defines tags that convey semantics
• We could write Health Markup Language (HML)
  in XML (if we could agree on the semantics and
  tags)
• Tags may or may not be stored with data

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ltdocumentgt lt/documentgt
ltdocument.idgtCXR001lt/document.idgt ltdoc.
dategt19991101lt/doc. dategt ltdocument.typegt lt/d
ocument.typegt ltdocument.bodygt ltdocument.bod
ygt
ltidentifiergtP5-00010lt/identifiergt
lttextgtChest X-Raylt/textgt
ltfindingsgtNo infiltrate, cardiac shadow not
enlarged...lt/findingsgt ltimpressiongtNormal
X-raylt/impressiongt
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ltpatientgt lt/patientgt
ltpatient.idgt lt/patient.idgt ltpatient.namegt lt/pa
tient.namegt ltpatient.dobgt19230113lt/patient.dobgt ltp
atient.sex value"male"/gt ltinpatient/gt
ltid.valuegt1234789lt/id.valuegt
ltfamily.namegtSandiegolt/family.namegt ltgiven.namegtCa
rmenlt/given.namegt ltsuffixgtM.D.lt/suffixgt
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Extensible Markup Language (XML) Databases

• Strengths
• Flexibility to represent wide range of data
• Data carries its field assignment
• Sparse data handled compactly
• Tags can have platform-specific display
• Weaknesses
• Immature database tools
• Verbose
• I/O intensive
• A trade-off of decreased efficiency for increased
  flexibility ? scalability

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Relational Databases - Advantages

• Comprehensible
• Multiple views possible
• Easy to modify
• New elements dont break programs
• Database management systems (DBMS)
• Referential integrity
• Reorg for efficiency
• Access control
• Locking for multiple simultaneous use

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Relational Databases - Disadvantages

• Storage overhead
• I/O-intense
• Cost