SlideShare a Scribd company logo
Introduction To Bioinformatics
 
After the Completion of This Course An appreciation  ___  the Huge data about Living things. Applications of BI  to  _____molecular biology, medicine, biotechnology, agriculture, forensic science, anthropology etc. Using the  WWW,   ____access the data and the methods for their analysis.
After the Completion of This Course  the role of computer science  in the    ___Analysis of the data ___ information retrieval,    ____ and the ability to extend these skills by  self-directed 'field work'  on the Web. A sense of optimism ____  Human Welfare
The Course Contents for Bioinformatics An Insight into Bioinformatics Biological Databases Bioinformatics for Gene(s) - Pairwise alignment Alignment of Multiple Sequences Searching sequence databases using BLAST FASTA Phylogenetic Analysis Hidden Markov models Gene Prediction, Micro arrays Bioinformatics for Protein(s) -Structure Prediction Dynamic programming applet Rasmol, Phylogeny, Multiple alignment
What Is Bioinformatics? Bioinformatics is the unified discipline formed from the combination of biology, computer science, and information technology. "The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.“ –Frank Tekaia
 
A Molecular Alphabet Most large  biological molecules are polymers , ordered chains of simple molecules called  monomers All  monomers belong to the same general class,  but there are several types the ordering of monomers  in the macromolecule encodes information, just like the  letters of an alphabet
Related Fields: Computational Biology The study and application of computing methods for classical biology Primarily concerned with evolutionary, population and theoretical biology, rather than the cellular or molecular level
Related Fields: Medical Informatics The study and application of computing methods to improve communication, understanding, and management of medical data Generally concerned with how the data is manipulated rather than the data itself
Related Fields: Cheminformatics The study and application of computing methods, along with chemical and biological technology,  for drug design and development
Related Fields: Genomics Analysis and comparison of the  entire  genome   of a single species or of multiple species A genome: set of all genes possessed by an organism
Related Fields: Proteomics Study of how the genome is expressed in proteins, and of how these proteins function and interact Concerned with the actual states of specific cells, rather than the potential states described by the genome
Related Fields: Pharmacogenetics The use of genomic methods to determine what causes variations in individual response to drug treatments The goal is to identify drugs that may  only be effective for subsets of patients, or to tailor drugs for specific individuals or groups
History of Bioinformatics Genetics Computers and Computer  Science Bioinformatics
History of Genetics Gregor Mendel  Chromosomes DNA
Gregor Mendel (1822-1884) theories of Heredity through the study of pea pods. Studied them  “ for the fun of the thing”
Mendel’s Experiments Cross-bred two different types of pea seads Sperical Wrinkled After the 2nd generation of pea seeds were cross-bred, Mendel noticed that, although all of the 2nd generation seeds were spherical,  about 1/4th of the 3rd generation seeds were wrinkled.
Mendel’s Experiments  (cont.) Through this, Mendel developed the concept of  “discrete units of inheritance,”  and that each individual pea plant had  two versions ,  or alleles , of a trait determining gene.
History of Chromosomes W Flemming A Weissman T Boveri W S. Sutton T H Morgan
Walther Flemming  (1843-1905) Studied the cells of salamanders and developing improved fixing and staining methods Developed the  concept of mitosis  (1882 ).
August Weismann ( 1834-1914) distinguished between  Soma cells and germ cells  theory of the continuity of germ plasm (1885) Developed the  concept of meiosis
Walter S. Sutton (1877-1916) Also studied germ cells specifically those of the  Brachystola magna  (grasshopper) Discovered that chromosomes carried the cell’s unit’s of inheritance
Thomas Hunt Morgan  (1866-1945) Studied the  Drosophilae  fruit fly to determine whether heredity determined Darwinist evolution Found that  genes could be mapped  in order along the length of a chromosome
History of DNA Griffith Avery, MacLeod, and McCarty Hershey and Chase Watson and Crick
Frederick Griffith  In 1928, Studied the effects of bacteria on mice Determined that some kind of “ transforming factor”  existed in the heredity of cells
Oswald Theodore Avery (1877-1955) Colin MacLeod  1944 - Through their work in bacteria, showed that  DNA was the transforming factor DNA  transferring genetic information Previously thought to be a protein
Alfred Hershey (1908-1997)  Martha Chase (1930-  ) 1952 - Studied the bacteriophage T2 and its host bacterium,  Escherichia coli   Found that DNA actually  is the genetic material  that is transferred
James Watson (1928-) Francis Crick (1916-) 1951 – Collaborated to gather all available data about DNA in order to determine its structure 1953 Developed  The double helix model for DNA structure The AT-CG strands that the helix is consisted of
" The structure was too pretty not to be true."  -- JAMES D. WATSON
Programable Mechanical  Computer
Computer Timeline ~1000BC The abacus 1621 The slide rule invented 1625 Wilhelm Schickard's  mechanical calculator 1822 Charles Babbage's Difference Engine  1926 First patent for a semiconductor transistor 1937 Alan Turing invents the Turing Machine 1939 Atanasoff-Berry Computer created at Iowa State  the world's first electronic digital computer  1939 to 1944 Howard Aiken's Harvard Mark I (the IBM ASCC) 1940 Konrad Zuse -Z2 uses telephone relays instead of mechanical logical circuits  1943 Collossus - British vacuum tube computer  1944 Grace Hopper, Mark I Programmer (Harvard Mark I)  1945 First  Computer "Bug",  Vannevar Bush "As we may think"  History of Computers
Computer Timeline (cont.) 1948 to 1951 The first commercial computer – UNIVAC 1952 G.W.A. Dummer conceives integrated circuits 1954 FORTRAN language developed by John Backus (IBM) 1955 First disk storage (IBM) 1958 First integrated circuit 1963 Mouse invented by Douglas Englebart 1963 BASIC (standing for  B eginner's  A ll Purpose  S ymbolic  I nstruction  C ode) was written (invented) at Dartmouth College, by mathematicians John George Kemeny and Tom Kurtzas as a teaching tool for undergraduates  1969 UNIX OS developed by Kenneth Thompson 1970 First static and dynamic RAMs 1971 First microprocessor: the 4004 1972 C language created by Dennis Ritchie 1975 Microsoft founded by Bill Gates and Paul Allen 1976 Apple I and Apple II microcomputers released 1981 First IBM PC with DOS 1985 Microsoft Windows introduced 1985 C++ language introduced 1992  Pentium processor 1993 First PDA 1994 JAVA introduced by James Gosling 1994 Csharp language introduced
Genomics Classic Genomics Post Genomic era Comparative Genomics Functional Genomics Structural Genomics
Genomics Genome complete set of genetic instructions for making an organism  Genomics any attempt to analyze or compare the entire genetic complement of a species  Early genomics was mostly recording genome sequences
History of Genomics 1980  First complete genome sequence for  adenovirus is published FX174 - 5,386 base pairs coding 9 proteins.  ~5Kb 1995  Haemophilus influenzea  genome  sequenced (flu bacteria, 1.8 Mb) 1996  Saccharomyces cerevisiae  (baker's yeast, 12.1 Mbp)  1997  E. coli  (4.7 Mbp)  2000 Pseudomonas aeruginosa  (6.3 Mbp)  A. thaliana genome (100 Mb)  D. melanogaster genome (180Mb)
2001 The Big One The Human Genome sequence is published 3 Gb
What next? Post Genomic era Comparative Genomics Functional Genomics Structural Genomics
What Is Proteomics? Proteomics is the study of the proteome—the  “PROTEin complement of the genOME” More specifically, "the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes"
What Makes Proteomics Important? A cell’s  DNA—its  genome—describes a  blueprint  for the  cell’s potential , all the possible forms that it could conceivably take.  It  does  not  describe the cell’s actual, current form,  in the same way that the source code of a computer program does not tell us what input a particular user is currently giving his copy of that program.
What Makes Proteomics Important ? All cells in an organism contain the same DNA. This DNA encodes every possible cell type in that organism—muscle, bone, nerve, skin, etc.
If we want to know about the type and state of a particular cell, the DNA does not help us,  in the same way that knowing what language a computer program was written in tells us nothing about what the program does.
What Makes Proteomics Important? Out of the thousands of genes, only a handful actually determine that cell’s structure. Many of the interesting things about a given cell’s current state can be deduced from the type and structure of the proteins it expresses. Changes in, for example, tissue types, carbon sources, temperature, and stage in life of the cell can be observed in its proteins.
Proteomics In Disease Treatment A large number of diseases are caused by a particular pattern in a group of genes. Isolating this group by comparing the hundreds of thousands of genes in each of many genomes would be very impractical. Looking at the proteomes of the cells associated with the disease is much more efficient.
Proteomics In Disease Treatment Many human diseases are caused by a normal protein being modified improperly. This also can only be detected in the proteome, not the genome. The targets of almost all medical drugs are proteins. By identifying these proteins, proteomics aids the progress of pharmacogenetics.
Examples What do these have in common? Alzheimer's disease Cystic fibrosis Mad Cow disease An inherited form of emphysema Even many cancers
Stanley Prusiner Prion Protein  is a normal protein frequent in living organisms.  When some prion change its shape by missfolding  it becomes Prion___  an  infectious agent     This is in contrast to all other known infectious agents, which must contain  nucleic acids   along with protein components.  Prions  come in different strains, each with a slightly different structure, and most of the time, strains breed true. Prion replication is nevertheless subject to occasional  epimutation  and then  natural  selection just like other forms of replication. [8]  However, the number of possible distinct prion strains is likely far smaller than the number of possible DNA sequences, so evolution takes place within a limited space.
 
 
 

More Related Content

PPTX
introduction of Bioinformatics
PPTX
Bioinformatics
PPTX
bioinformatics simple
PPTX
Bioinformatics
PPTX
Bioinformatics
PDF
Genomics and proteomics I
PPT
Bioinformatics in biotechnology by kk sahu
introduction of Bioinformatics
Bioinformatics
bioinformatics simple
Bioinformatics
Bioinformatics
Genomics and proteomics I
Bioinformatics in biotechnology by kk sahu

What's hot (20)

PPTX
Genomics
PPTX
Introduction to Bioinformatics
PDF
Gene prediction methods vijay
PPTX
PPTX
Protein databases
PPT
Bioinformatics in present and its future
PPT
Pubchem
PPTX
GENOMICS AND BIOINFORMATICS
PPTX
Protein database
PPT
Protein engineering
PPT
PPTX
Protein Databases
PPTX
Threading modeling methods
PPTX
2 whole genome sequencing and analysis
PPTX
Express sequence tags
PPT
Est database
PPTX
System biology and its tools
PPT
antisense technology
Genomics
Introduction to Bioinformatics
Gene prediction methods vijay
Protein databases
Bioinformatics in present and its future
Pubchem
GENOMICS AND BIOINFORMATICS
Protein database
Protein engineering
Protein Databases
Threading modeling methods
2 whole genome sequencing and analysis
Express sequence tags
Est database
System biology and its tools
antisense technology
Ad

Viewers also liked (20)

PPT
Application of Bioinformatics in different fields of sciences
PDF
1de2 semana europea sy s t organizaciones excelentes y felices
PPTX
Delivering Bioinformatics MapReduce Applications in the Cloud
PPT
Dr Justin Schonfeld - Bioinformatics Applications
PPT
Kallio Chipster Bosc2009
PDF
Caravane Bio [Mohammed Benbouida, AMBS, Morocco]
PPTX
Lt npsti process-and_forms_april_2011
PDF
الهوية الرقمية على مواقع التواصل الاجتماعي
PDF
Supporting bioinformatics applications with hybrid multi-cloud services
PDF
استراتيجيات العلوم والتكنولوجيا والتجديد العالمية المعاصرة (ST&I)
PPT
مهارات+1
PPTX
Present
PPTX
Dr. Dario Lijtmaer - Data Sharing/Collaboration and Publication using BOLD
PDF
e justice
PPTX
Visual Studio
PPTX
Brin bws13 quiz mmc
PDF
الثقافة المعلوماتية في الجامعات مكتبة جامعة 6 أكتوبر نوفمبر 2012م
PDF
تسويق خدمات المعلومات
PPS
From Sunset To Sunrise
PPT
الثقافة التقنية والمواطنة الالكترونية
Application of Bioinformatics in different fields of sciences
1de2 semana europea sy s t organizaciones excelentes y felices
Delivering Bioinformatics MapReduce Applications in the Cloud
Dr Justin Schonfeld - Bioinformatics Applications
Kallio Chipster Bosc2009
Caravane Bio [Mohammed Benbouida, AMBS, Morocco]
Lt npsti process-and_forms_april_2011
الهوية الرقمية على مواقع التواصل الاجتماعي
Supporting bioinformatics applications with hybrid multi-cloud services
استراتيجيات العلوم والتكنولوجيا والتجديد العالمية المعاصرة (ST&I)
مهارات+1
Present
Dr. Dario Lijtmaer - Data Sharing/Collaboration and Publication using BOLD
e justice
Visual Studio
Brin bws13 quiz mmc
الثقافة المعلوماتية في الجامعات مكتبة جامعة 6 أكتوبر نوفمبر 2012م
تسويق خدمات المعلومات
From Sunset To Sunrise
الثقافة التقنية والمواطنة الالكترونية
Ad

Similar to Bioinformatics lecture 1 (20)

PPT
Bioinformatics
PDF
Computer science history.pdf
DOCX
rheumatoid arthritis
PDF
Bioinformatics
PDF
Bioinformatics manual
PDF
Genomics
PPT
Introducción a la bioinformatica
PPT
Introduction-to-Bioinformatics-1.ppt
PPT
Bioinformatics for Computer Scientists.ppt
PPTX
Computational Genomics - Bioinformatics - IK
PPTX
MoM2010: Bioinformatics
PPTX
History and scope in bioinformatics
PPTX
Bioinformatics .pptx
PPT
Biotechnology
PPTX
Comparative genomics and proteomics
PPTX
Introduction to Bioinformatics: Part 2
PDF
LECTURE NOTES ON BIOINFORMATICS
PPTX
Introduction to bioinformaticsIntroduction to bioinformaticsIntroduction to b...
PPTX
DCIT_411_Lecture_1_Bioinformatics_Is.pptx
PPT
An Introductory lecture on BIOINFORMATICS
Bioinformatics
Computer science history.pdf
rheumatoid arthritis
Bioinformatics
Bioinformatics manual
Genomics
Introducción a la bioinformatica
Introduction-to-Bioinformatics-1.ppt
Bioinformatics for Computer Scientists.ppt
Computational Genomics - Bioinformatics - IK
MoM2010: Bioinformatics
History and scope in bioinformatics
Bioinformatics .pptx
Biotechnology
Comparative genomics and proteomics
Introduction to Bioinformatics: Part 2
LECTURE NOTES ON BIOINFORMATICS
Introduction to bioinformaticsIntroduction to bioinformaticsIntroduction to b...
DCIT_411_Lecture_1_Bioinformatics_Is.pptx
An Introductory lecture on BIOINFORMATICS

More from Hamid Ur-Rahman (20)

PPTX
Lecture 1 Bioinformatics Free Lecture Download
PPT
2nd semester L 01 Parsites causing des.ppt
PPT
Higher Order Protein Structures
PPT
Biomolecules: Peptides and Proteins
PPT
Biomolecules: Amino Acids and Peptides
PPT
Water, pH and Dissociation
PPT
Introduction to Medical Biochemistry
PPT
Pentose Phosphate Pathway (Hexose Monophosphate Shunt)
PPT
Hormonal Regulation: glycolysis/glucogenesis-Glucose homeostasis
PPT
Glycogen Metabolism and Control
PPT
Oxidative Phosphorylation
PPT
Ubiquinone (Coenzyme Q, or Q) Electron Carrier
PPT
Electron Transport and Oxidative Phosphorylation
PPT
Citric Acid Cycle-Anaplerosis
PPT
Citric Acid Cycle
PPT
Glycolysis
PPT
BioEnergetics
PPT
Zoological congres
PPT
Trophy hunting
PPT
Tick infestation majid m. m.
Lecture 1 Bioinformatics Free Lecture Download
2nd semester L 01 Parsites causing des.ppt
Higher Order Protein Structures
Biomolecules: Peptides and Proteins
Biomolecules: Amino Acids and Peptides
Water, pH and Dissociation
Introduction to Medical Biochemistry
Pentose Phosphate Pathway (Hexose Monophosphate Shunt)
Hormonal Regulation: glycolysis/glucogenesis-Glucose homeostasis
Glycogen Metabolism and Control
Oxidative Phosphorylation
Ubiquinone (Coenzyme Q, or Q) Electron Carrier
Electron Transport and Oxidative Phosphorylation
Citric Acid Cycle-Anaplerosis
Citric Acid Cycle
Glycolysis
BioEnergetics
Zoological congres
Trophy hunting
Tick infestation majid m. m.

Recently uploaded (20)

PDF
2.FourierTransform-ShortQuestionswithAnswers.pdf
PDF
Insiders guide to clinical Medicine.pdf
PDF
STATICS OF THE RIGID BODIES Hibbelers.pdf
PDF
Chapter 2 Heredity, Prenatal Development, and Birth.pdf
PPTX
Week 4 Term 3 Study Techniques revisited.pptx
PDF
102 student loan defaulters named and shamed – Is someone you know on the list?
PPTX
Introduction to Child Health Nursing – Unit I | Child Health Nursing I | B.Sc...
PDF
Basic Mud Logging Guide for educational purpose
PPTX
Introduction_to_Human_Anatomy_and_Physiology_for_B.Pharm.pptx
PPTX
master seminar digital applications in india
PPTX
Cell Types and Its function , kingdom of life
PDF
VCE English Exam - Section C Student Revision Booklet
PPTX
Renaissance Architecture: A Journey from Faith to Humanism
PDF
Module 4: Burden of Disease Tutorial Slides S2 2025
PPTX
IMMUNITY IMMUNITY refers to protection against infection, and the immune syst...
PDF
ANTIBIOTICS.pptx.pdf………………… xxxxxxxxxxxxx
PDF
Pre independence Education in Inndia.pdf
PDF
Anesthesia in Laparoscopic Surgery in India
PDF
O7-L3 Supply Chain Operations - ICLT Program
PPTX
PPH.pptx obstetrics and gynecology in nursing
2.FourierTransform-ShortQuestionswithAnswers.pdf
Insiders guide to clinical Medicine.pdf
STATICS OF THE RIGID BODIES Hibbelers.pdf
Chapter 2 Heredity, Prenatal Development, and Birth.pdf
Week 4 Term 3 Study Techniques revisited.pptx
102 student loan defaulters named and shamed – Is someone you know on the list?
Introduction to Child Health Nursing – Unit I | Child Health Nursing I | B.Sc...
Basic Mud Logging Guide for educational purpose
Introduction_to_Human_Anatomy_and_Physiology_for_B.Pharm.pptx
master seminar digital applications in india
Cell Types and Its function , kingdom of life
VCE English Exam - Section C Student Revision Booklet
Renaissance Architecture: A Journey from Faith to Humanism
Module 4: Burden of Disease Tutorial Slides S2 2025
IMMUNITY IMMUNITY refers to protection against infection, and the immune syst...
ANTIBIOTICS.pptx.pdf………………… xxxxxxxxxxxxx
Pre independence Education in Inndia.pdf
Anesthesia in Laparoscopic Surgery in India
O7-L3 Supply Chain Operations - ICLT Program
PPH.pptx obstetrics and gynecology in nursing

Bioinformatics lecture 1

  • 2.  
  • 3. After the Completion of This Course An appreciation ___ the Huge data about Living things. Applications of BI to _____molecular biology, medicine, biotechnology, agriculture, forensic science, anthropology etc. Using the WWW, ____access the data and the methods for their analysis.
  • 4. After the Completion of This Course the role of computer science in the ___Analysis of the data ___ information retrieval, ____ and the ability to extend these skills by self-directed 'field work' on the Web. A sense of optimism ____ Human Welfare
  • 5. The Course Contents for Bioinformatics An Insight into Bioinformatics Biological Databases Bioinformatics for Gene(s) - Pairwise alignment Alignment of Multiple Sequences Searching sequence databases using BLAST FASTA Phylogenetic Analysis Hidden Markov models Gene Prediction, Micro arrays Bioinformatics for Protein(s) -Structure Prediction Dynamic programming applet Rasmol, Phylogeny, Multiple alignment
  • 6. What Is Bioinformatics? Bioinformatics is the unified discipline formed from the combination of biology, computer science, and information technology. "The mathematical, statistical and computing methods that aim to solve biological problems using DNA and amino acid sequences and related information.“ –Frank Tekaia
  • 7.  
  • 8. A Molecular Alphabet Most large biological molecules are polymers , ordered chains of simple molecules called monomers All monomers belong to the same general class, but there are several types the ordering of monomers in the macromolecule encodes information, just like the letters of an alphabet
  • 9. Related Fields: Computational Biology The study and application of computing methods for classical biology Primarily concerned with evolutionary, population and theoretical biology, rather than the cellular or molecular level
  • 10. Related Fields: Medical Informatics The study and application of computing methods to improve communication, understanding, and management of medical data Generally concerned with how the data is manipulated rather than the data itself
  • 11. Related Fields: Cheminformatics The study and application of computing methods, along with chemical and biological technology, for drug design and development
  • 12. Related Fields: Genomics Analysis and comparison of the entire genome of a single species or of multiple species A genome: set of all genes possessed by an organism
  • 13. Related Fields: Proteomics Study of how the genome is expressed in proteins, and of how these proteins function and interact Concerned with the actual states of specific cells, rather than the potential states described by the genome
  • 14. Related Fields: Pharmacogenetics The use of genomic methods to determine what causes variations in individual response to drug treatments The goal is to identify drugs that may only be effective for subsets of patients, or to tailor drugs for specific individuals or groups
  • 15. History of Bioinformatics Genetics Computers and Computer Science Bioinformatics
  • 16. History of Genetics Gregor Mendel Chromosomes DNA
  • 17. Gregor Mendel (1822-1884) theories of Heredity through the study of pea pods. Studied them “ for the fun of the thing”
  • 18. Mendel’s Experiments Cross-bred two different types of pea seads Sperical Wrinkled After the 2nd generation of pea seeds were cross-bred, Mendel noticed that, although all of the 2nd generation seeds were spherical, about 1/4th of the 3rd generation seeds were wrinkled.
  • 19. Mendel’s Experiments (cont.) Through this, Mendel developed the concept of “discrete units of inheritance,” and that each individual pea plant had two versions , or alleles , of a trait determining gene.
  • 20. History of Chromosomes W Flemming A Weissman T Boveri W S. Sutton T H Morgan
  • 21. Walther Flemming (1843-1905) Studied the cells of salamanders and developing improved fixing and staining methods Developed the concept of mitosis (1882 ).
  • 22. August Weismann ( 1834-1914) distinguished between Soma cells and germ cells theory of the continuity of germ plasm (1885) Developed the concept of meiosis
  • 23. Walter S. Sutton (1877-1916) Also studied germ cells specifically those of the Brachystola magna (grasshopper) Discovered that chromosomes carried the cell’s unit’s of inheritance
  • 24. Thomas Hunt Morgan (1866-1945) Studied the Drosophilae fruit fly to determine whether heredity determined Darwinist evolution Found that genes could be mapped in order along the length of a chromosome
  • 25. History of DNA Griffith Avery, MacLeod, and McCarty Hershey and Chase Watson and Crick
  • 26. Frederick Griffith In 1928, Studied the effects of bacteria on mice Determined that some kind of “ transforming factor” existed in the heredity of cells
  • 27. Oswald Theodore Avery (1877-1955) Colin MacLeod 1944 - Through their work in bacteria, showed that DNA was the transforming factor DNA transferring genetic information Previously thought to be a protein
  • 28. Alfred Hershey (1908-1997) Martha Chase (1930- ) 1952 - Studied the bacteriophage T2 and its host bacterium, Escherichia coli Found that DNA actually is the genetic material that is transferred
  • 29. James Watson (1928-) Francis Crick (1916-) 1951 – Collaborated to gather all available data about DNA in order to determine its structure 1953 Developed The double helix model for DNA structure The AT-CG strands that the helix is consisted of
  • 30. " The structure was too pretty not to be true." -- JAMES D. WATSON
  • 32. Computer Timeline ~1000BC The abacus 1621 The slide rule invented 1625 Wilhelm Schickard's mechanical calculator 1822 Charles Babbage's Difference Engine 1926 First patent for a semiconductor transistor 1937 Alan Turing invents the Turing Machine 1939 Atanasoff-Berry Computer created at Iowa State the world's first electronic digital computer 1939 to 1944 Howard Aiken's Harvard Mark I (the IBM ASCC) 1940 Konrad Zuse -Z2 uses telephone relays instead of mechanical logical circuits 1943 Collossus - British vacuum tube computer 1944 Grace Hopper, Mark I Programmer (Harvard Mark I) 1945 First Computer "Bug", Vannevar Bush "As we may think" History of Computers
  • 33. Computer Timeline (cont.) 1948 to 1951 The first commercial computer – UNIVAC 1952 G.W.A. Dummer conceives integrated circuits 1954 FORTRAN language developed by John Backus (IBM) 1955 First disk storage (IBM) 1958 First integrated circuit 1963 Mouse invented by Douglas Englebart 1963 BASIC (standing for B eginner's A ll Purpose S ymbolic I nstruction C ode) was written (invented) at Dartmouth College, by mathematicians John George Kemeny and Tom Kurtzas as a teaching tool for undergraduates 1969 UNIX OS developed by Kenneth Thompson 1970 First static and dynamic RAMs 1971 First microprocessor: the 4004 1972 C language created by Dennis Ritchie 1975 Microsoft founded by Bill Gates and Paul Allen 1976 Apple I and Apple II microcomputers released 1981 First IBM PC with DOS 1985 Microsoft Windows introduced 1985 C++ language introduced 1992 Pentium processor 1993 First PDA 1994 JAVA introduced by James Gosling 1994 Csharp language introduced
  • 34. Genomics Classic Genomics Post Genomic era Comparative Genomics Functional Genomics Structural Genomics
  • 35. Genomics Genome complete set of genetic instructions for making an organism Genomics any attempt to analyze or compare the entire genetic complement of a species Early genomics was mostly recording genome sequences
  • 36. History of Genomics 1980 First complete genome sequence for adenovirus is published FX174 - 5,386 base pairs coding 9 proteins. ~5Kb 1995 Haemophilus influenzea genome sequenced (flu bacteria, 1.8 Mb) 1996 Saccharomyces cerevisiae (baker's yeast, 12.1 Mbp) 1997 E. coli (4.7 Mbp) 2000 Pseudomonas aeruginosa (6.3 Mbp) A. thaliana genome (100 Mb) D. melanogaster genome (180Mb)
  • 37. 2001 The Big One The Human Genome sequence is published 3 Gb
  • 38. What next? Post Genomic era Comparative Genomics Functional Genomics Structural Genomics
  • 39. What Is Proteomics? Proteomics is the study of the proteome—the “PROTEin complement of the genOME” More specifically, "the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes"
  • 40. What Makes Proteomics Important? A cell’s DNA—its genome—describes a blueprint for the cell’s potential , all the possible forms that it could conceivably take. It does not describe the cell’s actual, current form, in the same way that the source code of a computer program does not tell us what input a particular user is currently giving his copy of that program.
  • 41. What Makes Proteomics Important ? All cells in an organism contain the same DNA. This DNA encodes every possible cell type in that organism—muscle, bone, nerve, skin, etc.
  • 42. If we want to know about the type and state of a particular cell, the DNA does not help us, in the same way that knowing what language a computer program was written in tells us nothing about what the program does.
  • 43. What Makes Proteomics Important? Out of the thousands of genes, only a handful actually determine that cell’s structure. Many of the interesting things about a given cell’s current state can be deduced from the type and structure of the proteins it expresses. Changes in, for example, tissue types, carbon sources, temperature, and stage in life of the cell can be observed in its proteins.
  • 44. Proteomics In Disease Treatment A large number of diseases are caused by a particular pattern in a group of genes. Isolating this group by comparing the hundreds of thousands of genes in each of many genomes would be very impractical. Looking at the proteomes of the cells associated with the disease is much more efficient.
  • 45. Proteomics In Disease Treatment Many human diseases are caused by a normal protein being modified improperly. This also can only be detected in the proteome, not the genome. The targets of almost all medical drugs are proteins. By identifying these proteins, proteomics aids the progress of pharmacogenetics.
  • 46. Examples What do these have in common? Alzheimer's disease Cystic fibrosis Mad Cow disease An inherited form of emphysema Even many cancers
  • 47. Stanley Prusiner Prion Protein is a normal protein frequent in living organisms. When some prion change its shape by missfolding it becomes Prion___ an  infectious agent     This is in contrast to all other known infectious agents, which must contain  nucleic acids   along with protein components.  Prions come in different strains, each with a slightly different structure, and most of the time, strains breed true. Prion replication is nevertheless subject to occasional  epimutation  and then  natural selection just like other forms of replication. [8]  However, the number of possible distinct prion strains is likely far smaller than the number of possible DNA sequences, so evolution takes place within a limited space.
  • 48.  
  • 49.  
  • 50.  

Editor's Notes

  • #4: An appreciation ___ large amount of information about Living things. Applications of BI to _____molecular biology, medicine, pharmacology, biotechnology, agriculture, forensic science, anthropology etc. A useful knowledge of the techniques by which, through the WWW, we access the data and the methods for their analysis.
  • #5: A sense of optimism that the data and methods of bioinformatics will create profound advances in our understanding of life, and improvements in the health of humans and other living things.
  • #6: Molecular biology -Genetics & Protein Biochemistry
  • #10: Computational biology  involves the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. [1]  
  • #13: Genomics existed before any genomes were completely sequenced, but in a very primitive state
  • #15: Related Fields: Pharmacogenomics The application of genomic methods to identify drug targets For example, searching entire genomes for potential drug receptors, or by studying gene expression patterns in tumors i nvestigation of genetics and drug response: the study of the relationship between a specific person's genetic makeup and his or her response to drug treatment ( takes a singular verb ) Microsoft® Encarta® 2007. © 1993-2006 Microsoft Corporation. All rights reserved.
  • #18: theories of Heredity Developed his theories through the study of pea pods. Studied them “for the fun of the thing”
  • #20: This concept was later fully developed into the concept of chromosomes
  • #23: Studied plant and animal germ cells distinguished between body cells and germ cells and proposed the theory of the continuity of germ plasm from generation to generation (1885) Developed the concept of meiosis
  • #27: British microbiologist In 1928, Studied the effects of bacteria on mice Determined that some kind of “transforming factor” existed in the heredity of cells Frederick Griffith (1881-1941), British microbiologist who discovered a phenomenon called transformation—meaning an alteration of hereditary characteristics—in the Streptococcus pneumoniae bacterium. Griffith’s work paved the way for later experiments, which proved that deoxyribonucleic acid (DNA) is the material within cells that passes on genetic traits. He is considered by some to be the father of molecular biology. Avery's team purified this substance and found it was pure DNA. Avery published the results of his research in 1944. Transformation is the process by which bacteria take up unpackaged DNA from the environment. Only cells that are “competent” can receive DNA in this fashion. Cells can be made competent, however, via a routine procedure in molecular labs where introduction of foreign DNA into bacteria is fundamental to recombinant DNA technology. In transduction, viruses move DNA from one cell to another.
  • #29: Martha Chase: she participated in the famous “blender experiment,” also known as the Hershey-Chase experiment. This experiment, which earned Alfred Day Hershey a Nobel Prize, used a kitchen blender to separate the protein coats of simple viruses called bacteriophages from their DNA cores. Hershey and Chase showed that the isolated DNA was infectious, but that without the DNA, the protein coats were not. Microsoft ® Encarta ® 2007. © 1993-2006 Microsoft Corporation. All rights reserved.
  • #37: 1980: submission of the whole genome sequence of adenovirus to GenBank(R), the National Institutes of Health genetic sequence database. The submission marks the first time that a new method has been used to sequence a whole genome since Walter Gilbert and Frederick Sanger won the Nobel Prize in 1980 for the invention of DNA sequencing in 1977. The whole genome sequence (GenBank accession nos. AY370909, AY370910, and AY370911) was generated in less than one day using the first technology ever designed to sequence whole genomes, not one gene at a time. More importantly, this was accomplished by using a new platform that is scaleable to larger genomes. The bacteriophages Rt7 and Qβ have RNA as their genetic material. The single stranded RNA contains only three genes, One codes for A protein the second for coat protein, and the third for one of four subunits of replicase. (The other three units of replicase are host proteins). Polyoma or SV40 viruses have 5-10 genes and their chromosomes are only 1.7 microns in length. The single stranded DNA virus ØX174 has DNA which codes for 9 Proteins. The bacterial virus lambda has about 40 genes and T4 has over a hundred genes. The number of genes in viruses ranges from only three in the simplest viruses to about 250 in the most complex ones.
  • #38: Although there is some relationship between the number of genes and the complexity of an organism there in no strict correlation between apparent genetic complexity and the DNA content per haploid nucleus. Thus some fishes and amphibians contain 10 to 20 times more DNA than humans. Moreover, the size of the genome varies over a 20-fold range within the species of a phylum kilo base pairs = 1000 bp; Mb =  mega base pairs  = 1000000 bp; 1 million bp GBP: 1000 million bp
  • #39: Comparative Genomics: the management and analysis of the millions of data points that result from Genomics__ Sorting out the mess Functional Genomics: identifying gene functions and associations Strucutural Genomics: future plans of structural genomics efforts around the world and describes the possible benefits of this research
  • #42: Recall the concept of differentiation from embryology.
  • #44: The haploid human genome contains ca. 23,000 protein-coding genes , far fewer than had been expected before its sequencing. [1][2]  In fact, only about 1.5% of the genome codes for  proteins , while the rest consists of  non-coding RNA  genes, regulatory sequences ,  introns , and  noncoding DNA  (once known as "junk DNA"). [3] Surprisingly, the number of human genes seems to be less than a factor of two greater than that of many much simpler organisms, such as the  roundworm  and the  fruit fly . However, human cells make extensive use of  alternative splicing  to produce several different proteins from a single gene, and the human  proteome  is thought to be much larger than those of the aforementioned organisms.[ citation needed ] Besides, most human genes have multiple  exons , and human  introns  are frequently much longer than the flanking exons.[ citation needed ]
  • #47: Prions epigenetics  is the study of  heritable  changes in  phenotype  (appearance) or  gene expression  caused by mechanisms other than changes in the underlying  DNA  sequence, hence the name  epi-  (Greek:  επί - over, above)  - genetics . These changes may remain through  cell   divisions  for the remainder of the cell's life and may also last for multiple generations. However, there is no change in the underlying  DNA  sequence of the organism; [1]  instead, non-genetic factors cause the organism's genes to behave (or "express themselves") differently. [2] One example of epigenetic changes in  eukaryotic  biology is the process of  cellular differentiation . During  morphogenesis , totipotent   stem cells  become the various  pluripotent   cell lines  of the  embryo  which in turn become fully differentiated cells. In other words, a single fertilized egg cell – the  zygote  – changes into the many cell types including neurons, muscle cells, epithelium, blood vessels etc. as it continues to  divide . It does so by activating some genes while inhibiting others
  • #48: The normal role of Prions is not known. It probably protects cells from injury. All known mammalian prion diseases are caused by the so-called prion protein,  PrP . The endogenous, properly-folded, form is denoted PrPC (for  c ommon  or  c ellular ) while the disease-linked, misfolded form is denoted PrPSc (for  Sc rapie , after one of the diseases first linked to prions and neurodegeneration.) [9][10]  The precise structure of the prion is not known, though they can be formed by combining PrPC, polyadenylic acid, and lipids in a  Protein Misfolding Cyclic Amplification  (PMCA) reaction. [11] Proteins showing prion-type behavior are also found in some  fungi , which has been useful in helping to understand mammalian prions. Interestingly,  fungal prions  do not appear to cause disease in their hosts and may even confer an evolutionary  advantage through a form of protein-based  inheritance . [12]