bioinformatics a communication/signal processing...
TRANSCRIPT
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Bioinformatics A Communication/Signal Processing Perspective
Khalid Sayood
Occult Information Lab
Department of Electrical and Computer
Engineering
University of Nebraska-Lincoln
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Outline
• Beginning
• Middle
• End
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My roots
• Signal Processing
• Communication
• Information Theory
• Data Compression
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My roots
• Data Compression - The art or science of finding compact
representations of information in data
• Speech Images Video DNA
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DNA
RNA transcript with cap and tail
mRNA
Exon Intron Intron Exon Exon
Transcription Addition of cap and tail
Introns removed
Exons spliced together
Coding sequence
NUCLEUS
CYTOPLASM
Tail
Cap
Prokaryotes
Eukaryotes
Analogy to Communications:
Start, Message, Stop
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Definitions of Bioinformatics
• Original definition: Study of informatic processes in biotic systems – Pauline Hogeweg and
Ben Hesper
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Definitions of Bioinformatics
• Original definition: Study of informatic processes in biotic systems – Pauline Hogeweg and
Ben Hesper
• Bioinformatics is conceptualizing biology in terms of molecules (in the sense of physical-
chemistry) and then applying i for atics techniques (derived from disciplines such as
applied math, CS, and statistics) to understand and organize the information associated with
these molecules, on a large-scale. (Mark Gerstein, 1999)
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.
Data Storage and
Management Data Analysis Interpretation
of Results
Molecular Sequence
Analysis
• Homology Search
• Phylogeny Construction
• Whole Genome
Sequencing
• Gene Finding
Protein Structure
Prediction
•Protein/RNA tertiary
structure
•Docking
•Drug Design
Functional
Genomics and
Proteomics
• Microarrays
• Biomarker
Discovery
Systems Biology
•Pathways
•Network based
wholistic approach
Bioinformatics is a management and analysis information system for life sciences.
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Fro
m R
NA
-seq
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ds to
diffe
ren
tial e
xp
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n re
sults
•Alicia
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Preprocessing:
FastQC
Trimmomatic
Indexing the Reads:
Bowtie 2
Aligning to hg19/KSHV
TopHat 2
Local alignment
Extracting Features
CuffDiff
P < 0.01
FPKMs values
Differentially Expressed Genes
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Ap
ach
e T
ave
rna
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Wa
ge
nin
ge
n U
niv
ersity
an
d R
ese
arch
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So what is the problem?
• What is actually going on.
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Is there hope (for me)?
Digital Camera (1975) Genome Sequencer (2018)
Hope springs eternal
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What do we mean by a Communication Theory
Perspective
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Information exists in the form of a stochastic process
What do we I mean by a Communication Theory
Perspective
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How do we deal with stochastic processes?
• Look at the signal using different basis sets – frequency domain processing.
• Look at correlation structures.
• Look at models.
All these involve averaging of some sort
All these result in the discovery of underlying structure
They can also result in dimensionality reduction.
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Realizations of a stochastic process
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Frequency profile
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Statistical Profile
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Models
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But we have sequences – we don’t have numbers
GAGACATTCAGTG
G
C
T
A
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But we have sequences – we don’t have numbers
GAGACATTCAGT
A
C
G
T
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But we have sequences – we don’t have numbers
G A G A C A T T C A G T G
A 0 1 0 1 0 1 0 0 0 1 0 0 0
C 0 0 0 0 1 0 0 0 1 0 0 0 0
G 1 0 1 0 0 0 0 0 0 0 1 0 1
T 0 0 0 0 0 0 1 1 0 0 0 1 0
Identification of Protein Coding Regions Using the
Modified Gabor-Wavelet Transform Mena-Chalco et al. IEEE/ACM Trans. Comp. Bio
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But we have sequences – we don’t have numbers
AA AC AG AT CA CC CG CT GA GC GG GT TA TC TG TT
0 1 2 1 2 0 0 0 2 0 0 1 0 1 1 1
G A G A C A T T C A G T G
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But we have sequences – we don’t have numbers
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AMI Profile for Human Chromosome 1
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Human chromosomes
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Mouse Chromosome
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C. Elegans Chromosome
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• Phylogeny for Candida and
Saccharomyces clades based
on multiple sequence
alignment of 706 orthologous
genes
• Posterior probabilities shown
• WGD: Whole Genome
Duplication
• CTG: Translation of CTG codons
as serine rather than leucine
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• Ribosomal DNA (rDNA) is commonly used to evaluate species relatedness
• The rDNA gene complex contains 3 genes, each of which are ribosomal
components once transcribed
• Internal transcribed spacer (ITS) 1 and ITS2 separate these genes
• ITS regions have 2 benefits:
1. Easy to design primers (ribosome genes highly conserved, many
copies)
2. Spacers diverge more quickly than ribosome genes
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• Distance matrix D generated by calculating pairwise distance dij
between AMI profiles xi and xj
• Distance defined in two ways:
1. Correlation distance (angle between profiles) 𝑑 = 1 − cos 𝜃 = 1 − 𝒙 ∙ 𝒙𝒙 𝒙
2. Euclidean distance 𝑑 = 𝒙 − 𝒙
• Phylogenetic trees generated using PHYLIP (neighbor joining)
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GO Prediction
BP: Biological Processes, CC: Cellular Component, MF: Molecular Function
“High Abundance" GO terms “Low Abundance” GO terms
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M E W S I N A N Q M Q L D Y Q R T R L K
M D C F I R S K H L K L G H Q H I H L N
M D G S I N A N Q M N F G H Q R I H L K
M D C S E N A K Y I K L A Q H R I H L N
M E C S I N A N Q R N L G H Q R I Y L K
M D W S I N A N H M K L D R P Q I H L T
M D C S I N A N Q I K F A Q Q R M H L N
M E C S E N A K R M K S G H Q H I H F K
M D G S I N A N Q K I L G H H R I Q L R
M Q C S I N A N H K K F G Q Q R T H L K
M D G E N A K H I K L D Q H R I Q L N
M R C S T M D N Q M N L G R Q H I H F K
S
k m
M D C S I N A N Q M K L G H Q R I H L K
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Slow progressor populations Rapid progressor populations
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Metagenomics
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𝑝 , =𝐺 ∩𝐺𝐺
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RRMSE for the simulated metagenomes corresponding to a mixture of 10, 20, 50, and 100 randomly
selected organisms for 0.01X and 0.1X average genome coverages.
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Oc
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In
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at
ion
La
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Bio
inf
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ma
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s
Mark Bauer Hasan Otu David Russell Ufuk Nalbantoglu Sam Way
Amirsalar Mansouri Garin Newcomb Dicle Yalcin Keith Murray Jacob Bohac
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