FINALbioinformatics SEMINAR

8/12/2019 FINALbioinformatics SEMINAR

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BIOINFORMATICS & COMPUTING

METHODS

Presented by:

Sudhakar TripathiResearch scholar

Computer Engineering Department

IT-BHU

Supervisor:

Prof. R.B.Mishra


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Bioinformatics Definition

An interdisciplinary field involving biology,

computer science, mathematics and statistics

to analyze biological sequence data, genome

content, arrangement and to predict the

function & structure of macromolecules.

-David C. Mount


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What is Bioinformatics?

The creation and development of advanced

information and computational technologies

for problems in biology, most commonly

molecular biology (but increasingly in otherareas of biology). As such, it deals with

methods for storing, retrieving and analyzing

biological data, such as nucleic acid(DNA/RNA) and protein sequences, structures,

functions, pathways and genetic interactions.


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Need for and Use of Bioinformatics

Bioinformatics plays a key role in modern biology and is especially important

in:

_Molecular biology

_Genomics

_Functional genomics

_Systems biology

_Protein design and engineering

_Pharmaceutical development

_Medicine

_Ecology / population genetics

Need for and Use of Bioinformatics

_Finding genes, locating coding regions, predicting function

_Function, Evolution, Sequence, Structure (FESS relationships)

_Metabolic genotype, phenotype, redundancy

_Genes to Pathways; Genes to Biological Knowledge

_Proteomics: Proteome of an Organism

_Assigning Gene Sets to different Species: Homologs vs Paralogs

_Expression profiles, relation to Metabolic Pathways / Genetic Networks

Experimentally Analyse Thousands of Genes simultaneously

_Gene Synteny between Species: Gene Adjacency in Genomes

_Polymorphisms, Haplotypes, Propensity for Genetic Disease

-Searching databases for nucleotide or amino acid sequences that match sequences in unknownsamples

Inferring a proteins shape and function from a given a sequence of amino acids,

Finding all the genes and proteins in a given genome,

Determining sites in the protein structure where drug molecules can beattached.


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Aim of research in Bioinformatics

Understand the functioning of living things - to

improve the quality of life.

drug design

identification of genetic risk factors

gene therapy

genetic modification of food crops and animals, etc.

application to e.g. biotechnology

How will this benefit humanity !

Genetically modified crops ! - contamination escapes

Genetically modified " & #- whisky? "

Genes & behaviour - really?

Testing on animals - why? $% Gene therapy &'benefits outweigh dangers? (

Bio weapons? # ) * +


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Genetic material

Information transfer (mRNA)

Protein synthesis (tRNA/mRNA)

Some catalytic activity

Most cellular functions are performed or facilitated by proteins.

Primary biocatalyst Cofactor transport/storage

Mechanical motion/support

Immune protection

Control of growth/differentiation

Genome Sequence

Finding Genes in Genomic DNA

introns

exons

promotors

Characterizing Repeats in

Genomic DNA

Statistics

Patterns

Duplications in the Genome


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The Complexity of Biological Data

Nucleotide sequences Nucleotide structures

Gene expressions

Protein Structures

Protein functions Protein-protein interaction (pathways)

Cell

Cell signaling

Tissues Organs

Physiology

Organisms


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Basic cell architectureCells are smallest functional units of life


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Types of cell

Prokaryotes Eukaryotes

Single cell Single or multi cell

No nucleus Nucleus

No organelles Organelles

One piece of circular DNA(plasmid)

Chromosomes

No mRNA post transcriptional

modification

Exons/Introns splicing


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ProteinsProteins are biological molecules of primary importance to the functioning of

livingOrganisms Perform many and varied functions

Structural Proteins: the organism's basic building blocks, eg. collagen, nails, hair, etc

Enzymes:biological engines which mediate multitude of biochemical reactions. Usually

enzymes are very specific and catalyze only a single type of reaction, but they can play a

role in more than one pathway.

Transmembrane proteins: they are the cells housekeepers, eg. By regulating cell

volume, extraction and concentration of small molecules from the extracellular

environment and generation of ionic gradients essential for muscle and nerve cellfunction (sodium/potasium pump is an example)

U d t di t i t t i k t d t di f ti d d f ti


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Understanding protein structure is key to understanding functionand dysfunctionAmino Acid Sequences AAs polymerised into Chains (Residues)

Gene sequence determines Protein sequence

Protein Structure Chains fold into specific compact structures

Structure formation (folding) is spontaneous

Sequence determines Structure

Structure determines function


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Information flow in the cell - Central Dogma

DNA (4 bases, {A,C,G,T}) transcribed into

RNA (4 bases, {A,C,G,U}) translated into

Protein (20 amino acid residues,

{A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y}) by triplets

(codons) of RNAs

UCA -> Serine (S)Start codon AUG -> Methionine (M)

3 stop codons (UGA, UAA,UAG) in most species

As always in Biology, there are exceptions!

Some species use different stop codons. The codon table(codon -> AA) is not the same for

all species, the mitochondria has different codon table.


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How DNA Codes for Protein


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Various Problem areas in Bioinformatics

Sequencing

Sequence analysis

Sequence alignment

The RNA Secondary Structure Prediction

Identifying Gene Regulatory Networks

Protein structure analysis

Protein structure comparision

Protein folding

domain pattern recognition

Sequence representation

Genotype Analysis

Splicing Site prediction
http://en.wikipedia.org/wiki/Genotypinghttp://en.wikipedia.org/wiki/RNA_splicinghttp://en.wikipedia.org/wiki/RNA_splicinghttp://en.wikipedia.org/wiki/Genotyping


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Protein - protein interaction

Database development

Modeling genetics History

Ancient DNA

cDNAs

Population Genetics Simulations

Finding SNPs Genome wide Association Studies

Homology Search

The Sequence DB Search problem

Efficient searching in large data sets interfacing with data to support genomics research - software,

databases, and

HGT Analysis


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Finding signal in the datasets - statistical and computational

methods

Need to get more efficient in how the data is processed,

organized, and accessed

how do we represent the large amount of data? Dynamically

and interactively?

Gene network reconstruction from time series data

Gene function prediction

Clustering of Gene Expression Data

Characterization of Metabolic Pathways between Different

Genomes

Organizing biological knowledge in databases

Signal transduction and other biochemical pathways

Phylogenetics:Predicting the genetic or evolutionary relation

of set of organisms.

Alternative splicing
http://en.wikipedia.org/wiki/Phylogeneticshttp://en.wikipedia.org/wiki/Phylogenetics


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Alternative splicing

Gene disease relationships

Microarray data collection, calibration and analysis

Polymorphism Analysis and visualization Pathway Analysis:Sequence comparison,Searches in sequence

databases

Sequence Matching:Tracing Phylogeny,Finding family

relationships between species by tracking, similarities betweenspecies.

Molecular Networks

Protein Threading

Sequence Comparisons and Sequence-Based Database Searches Clinical Diagnosis

Gene Expression Prediction

Genetic Linkage Analysis

Protein Function Prediction


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Various Computational methods

used in Bioinformatics

Mathematical Computing methodsStatistical computing methods

I ntell igent Computing methods

Neural Network Approaches

Integrated Differential Fuzzy Clustering

Fuzzy Computing

Genetic and Evolutionary Computing Algorithms

Probabilistic Computing and Belief Networks

HYBRID INTELLIGENT SYSTEMS

Swarm Intelligence

Rough Set Theory

Granular ComputingArtificial Immune Systems

Chaos Theory

The Differential Evolution Algorithm

Soft Computing

Dynamic Programming & various Algorithmic Computations


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Gene Prediction

Overview of steps & strategies

What sequence signals can be used?

What other types of information can be used?

Algorithms

HMMs, discriminant functions, neural nets

Gene prediction software

3 major types

many,many programs!


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Overview of gene prediction strategies

What sequence signals can be used? Transcription:TF binding sites, promoter,

initiation site, terminator

Processing signals:splice donor/acceptors, polyA signal

Translation: start (AUG = Met) & stop (UGA,UUA,UAG)

ORFs, codon usage

What other types of information can be used?

cDNAs & ESTs(experimental data,pairwise alignment) homology(sequence comparison, BLAST)


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Examples of gene prediction software

1) Similarity-based or Comparative

BLAST

SGP2 (extension of GeneID)

2) Ab initio = from the beginning

GeneID

GENSCAN

GeneMark.hmm

3) Combined "evidence-based

GeneSeqer(Brendel et al., ISU)

BEST? GENSCAN, GeneMark.hmm, GeneSeqer

but depends on organism & specific task


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Signals: Pre-mRNA Splicing

Translation

Protein

Splicing

mRNA Cap- -Poly(A)

Transcription

pre-mRNA Cap- -Poly(A)

Genomic DNA

Start codon Stop codon

GT AG

exon intron

Splice sites

Donor site Acceptor

site


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Post Transcription Splicing

Genomic DNA


mRNA -Poly(A)Cap-

5-UTR3-UTR



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Horizontal Gene Transfer

The movement of genetic material BETWEENprokaryotes

Common in prokaryotes. Useful forenvironmental adaptation (better than pointmutations)


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PHYLOGENY


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Homology & Similarity

Homology Conserved sequences arising from a common ancestor

Orthologs:homologous genes that share a commonancestor in the absence of any gene duplication (Mouse

and Human Hemoglobin) Paralogs:genes related through gene duplication (one

gene is a copy of another - Fetal and Adult Hemoglobin)

Similarity Genes that share common sequences but are not

necessarily related


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Phylogenetics

What is Phylogenetics?

Science of identifying and interpreting

evolutionary relationships between biological

entities (species, genes, etc)

What is a phylogenetic tree?

Dendrogram (tree) composed of nodes and

branches representing the putative geneology

of the taxonomic units


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Phylogenetic Trees

A Graph Representing The Evolutionary History Of

Sequences

Relationship of sequences to one another (How everythingis connected)

Dissect the order of appearance of insertions, deletions,and mutations

Identify Related Sequences, Predict Function,

Observe Epidemiology (Analyze changes in viralstrains)


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Tree Characteristics

Tree Properties Clade:all the descendants of a common ancestor

represented by a node

Distance:number of changes that have taken place

along a branch

Tree Types Cladogram:shows the branching order of nodes

Phylogram:shows branching order and distances

A

B

C

D

.035

.009

.057

.044

.012

.016

Phylogram


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Methods

Distance-based

Parsimony

Maximum likelihood


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Levels of Protein Structure

Primary (1) structure: amino acid sequence of

protein

Secondary (2) structure: local structure (alpha

helices or beta strands)

Tertiary (3) structure: 3-dimensional structure

of protein

Quaternary (4) structure: structure of a

multiple protein complex


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Protein structures Prediction

protein structures can be determined

experimentally (in most cases) by

x-ray crystallography

nuclear magnetic resonance (NMR) but this is very expensive and time-consuming

can we predict structures by computational

meansinstead?

PDB Content Growth

Methods for Secondary Structure


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Methods for Secondary StructurePrediction

Chou-Fasman method

Based on the propensities of different amino acids to adoptdifferent

secondary structures

Predictions are made using a rules-based approach toidentify groups of

amino acids with shared secondary structure propensities Garnier, Osguthorpe, Robson (GOR) method

Statistical method of secondary structure prediction basedon informationtheory & Bayesian probability

Multiple Sequence Alignment (MSA) methods

Performs secondary structure prediction on a multiplesequence alignment as opposed to a single protein sequence

Neural network-based methods

Example: Profile network from Heidelberg (PHD)

M th d f T ti St t


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Methods for Tertiary Structure

Prediction

Tertiary (3D) Structure Prediction

Homology Modeling

Fold Recognition Protein Threading

Ab initio structure prediction

Quaternary Structure


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THANKS!

Documents

FINALbioinformatics SEMINAR