lecture 1 n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Lecture 1 PowerPoint Presentation
Download Presentation
Lecture 1

Loading in 2 Seconds...

play fullscreen
1 / 20

Lecture 1 - PowerPoint PPT Presentation


  • 79 Views
  • Uploaded on

Bioinformatics. Lecture 1. What is bioinformatics? Why bioinformatics? The major molecular biology facts Brief history of bioinformatics Typical problems of bioinformatics: collection and retrieval of data alignment and similarity search prediction and classification

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Lecture 1' - sabine


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
lecture 1

Bioinformatics

Lecture 1
  • What is bioinformatics?
  • Why bioinformatics?
  • The major molecular biology facts
  • Brief history of bioinformatics
  • Typical problems of bioinformatics:
  • collection and retrieval of data
  • alignment and similarity search
  • prediction and classification
  • Expectationsand the level of requirements
what is bioinformatics
What is Bioinformatics?

Computer Science

Mathematics and Statistics

Biology

what is bioinformatics1
What is bioinformatics?

A working definition is that of House of Representatives Standing Committee on Primary Industries and Regional Services Inquiry :-

"All aspects of gathering, storing, handling, analyzing, interpreting and spreading vast amounts of biological information in databases. The information involved includes gene sequences, biological activity/function, pharmacological activity, biological structure, molecular structure, protein-protein interactions, and gene expression. Bioinformatics uses powerful computers and statistical techniques to accomplish research objectives, for example, to discover a new pharmaceutical or herbicide."

areas of current and future development of bioinformatics
Areas of current and future development of bioinformatics
  • Molecular biology and genetics
  • Phylogenetic and evolutionary sciences
  • Different aspects of biotechnology including pharmaceutical and microbiological industries
  • Medicine
  • Agriculture
  • Eco-management
why bioinformatics
Why bioinformatics?
  • Exponential growth of investments
  • Constant deficit of trained professionals
  • Diversification of bioinformatics applications
  • Need in different types of bioinformaticians
central dogma of molecular biology
Central Dogma of Molecular Biology

replication

GENOTYPE (i.e. Aa)

GENE (DNA)

ATGCAAGTCCACTGTATTCCA

reverse tr

transcription

MESSENGER (RNA)

UACGUUCAGGUGACAUAAGGG

translation

PROTEIN

PHENOTYPE (pink)

TRAIT

slide7

A C G T C A T G

5’

3’

3’

5’

T G C A G T A C

DNA

template

Symbol Meaning Explanation

G G Guanine

A A Adenine

T T Thymine

C C Cytosine

R A or G puRine

Y C or T pYrimidine

N A, C, G or T Any base

RNA

Double helix

A C G U C A U G

5’

3’

U U Uracil

slide8

Genetic Code

  • Amino acids are coded by codons – triplets of nucleotides, e.g. |ACG|TAT|….
  • There are 43 = 64 codons for ~20 amino acids, the code is degenerate
  • Codons do not overlap
  • Deletions or insertions of one or few nucleotides (not equal to 3 x N) usually destroy a message by shifting a reading frame
  • Three specific codons (stop codons) do not code any amino acid and are always located at the very end of the protein coding part of a gene
proteins

Green Fluorecent Protein (GFP)

PROTEINS

1 mcgkkfelki dnvrfvghpt llqpphtiqa sktdpspkre lptmilfsvv falranadas

61 viscmhnlsr riaialqhee rrcqyltrea klmlamqdev ttiidsdgsp qspfrqilpk

121 cklardlkea ydslcttgvv rlhinnwlev sfclphkihr vggkhiplea lerslkairp

genomic hierarchy in eukaryotes
Genomic Hierarchy in Eukaryotes

Genome nuclear (1)

Chromosomes (23x2)

DNA molecules (23x2)

Genes (~30,000); only a small fraction of genome

Nucleotides (~3x109)

eukaryotic genes are complex
Eukaryotic genes are complex

Start codonIntron 1 Intron 2 Intron 3 Stop codon

Promoter Exon 1 Exon 2 Exon 3 Exon 4

Protein codingregions

brief history of bioinformatics databases
Brief history of bioinformatics: Databases
  • The first biological database - Protein Identification Resource was established in 1972 by Margaret Dayhoff
  • Dayhoff and co-workers organized the proteins into families and superfamilies based on degree of sequence similarity
  • Idea of sequence alignment was introduced as well as special tables that reflected the frequency of changes observed in the sequences of a group of closely related proteins
  • Currently there are several huge Protein Banks : SwissProt, PIR International, etc.
  • The first DNA database was established in 1979. Currently there are several powerful databases: GenBank, EMBL, DDBJ, etc.
brief history of bioinformatics other important steps
Brief history of bioinformatics: other important steps
  • Development of sequence retrieval methods (1970-80s)
  • Development of principles of sequence alignment (1980s)
  • Prediction of RNA secondary structure (1980s)
  • Prediction of protein secondary structure and 3D (1980-90s)
  • The FASTA and BLAST methods for DB search (1980-90s)
  • Prediction of genes (1990s)
  • Studies of complete genome sequences (late 1990s –2000s)
collection and retrieval of data alignment methods
Collection and retrieval of data. Alignment methods.
  • Sequencing (DNA, proteins)
  • Submission of sequences to the databases
  • Computer storage of sequences
  • Development of sequence formats
  • Conversion of one sequence format to another
  • Development of retrieval and alignment methods
prediction reconstruction and classification
Prediction, reconstruction and classification
  • Prediction of secondary and 3D structure of RNA and proteins
  • Gene prediction in prokaryotes and eukaryotes
  • Prediction of promoters and other functional sites
  • Reconstruction of phylogeny
  • Genome analysis
  • Classification of proteins and genes
prediction of rna secondary structure an example

3’

5’

5’3’

Prediction of RNA secondary structure: an example

A. Single stranded RNA

B. Stem and loop or hairpin loop

expectations of students performance
Expectations of students’ performance
  • Basic understanding of general principles of molecular biology
  • Some mathematical and computer science background
  • Focus on using computational methods and understanding
  • general ideas of analysis used in bioinformatics
  • Formal description of algorithms and complex methodology
  • will not be the core elements of this unit
  • The core requirement is understanding of foundations of
  • bioinformatics and “hands on” approach