Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0

Learning Life through Bioinformatics…
What is Bioinformatics?
What is Bio-Bio-1?
Fokhruz Zaman
Founder & Evangelist, Bio-Bio-1
4th
July, 2013; UODA BI Workshop, Dhaka

4th July, 2013 Bioinformatics Workshop @ UODA, Dhaka
2

Finding patterns in molecular biological data
Implies:
• managing molecular biological data
• identifying correlations in molecular biological
data
Goals:
• characterise biological patterns & processes
• predict biological properties
3

Bioinformatics: neighbour disciplines
• Computational biology
– Broader concept: includes computational ecology,
physiology, neurology etc...
• -omics:
– Genomics
– Transcriptomics
– Proteomics
• Systems biology
– Putting it all together...
– Building models, identify control & regulation
4

Bioinformatics: prerequisites
• Bio- side:
– Molecular biology
– Cell biology
– Genetics
– Evolutionary theory
• -informatics side:
– Computer science
– Statistics
– Theoretical physics
5

Central Dogma of Molecular Biology
GENOTYPE (i.e. Aa)
PHENOTYPE (pink)
GENE (DNA)
MESSENGER (RNA)
PROTEIN
TRAIT
ATGCAAGTCCACTGTATTCCA
UACGUUCAGGUGACAUAAGGG
transcription reverse tr
translation
replication
6

Molecular biology data...
>al pha- D
ATGCTGACCGACTCTGACAAGAAGCTGGTCCTGCAGGTGTGGGAGAAGGTGATCCGCCAC
CCAGACTGTGGAGCCGAGGCCCTGGAGAGGTGCGGGCTGAGCTTGGGGAAACCATGGGCA
AGGGGGGCGACTGGGTGGGAGCCCTACAGGGCTGCTGGGGGTTGTTCGGCTGGGGGTCAG
CACTGACCATCCCGCTCCCGCAGCTGTTCACCACCTACCCCCAGACCAAGACCTACTTCC
CCCACTTCGACTTGCACCATGGCTCCGACCAGGTCCGCAACCACGGCAAGAAGGTGTTGG
CCGCCTTGGGCAACGCTGTCAAGAGCCTGGGCAACCTCAGCCAAGCCCTGTCTGACCTCA
GCGACCTGCATGCCTACAACCTGCGTGTCGACCCTGTCAACTTCAAGGCAGGCGGGGGAC
GGGGGTCAGGGGCCGGGGAGTTGGGGGCCAGGGACCTGGTTGGGGATCCGGGGCCATGCC
GGCGGTACTGAGCCCTGTTTTGCCTTGCAGCTGCTGGCGCAGTGCTTCCACGTGGTGCTG
GCCACACACCTGGGCAACGACTACACCCCGGAGGCACATGCTGCCTTCGACAAGTTCCTG
TCGGCTGTGTGCACCGTGCTGGCCGAGAAGTACAGATAA
>al pha- A
ATGGTGCTGTCTGCCAACGACAAGAGCAACGTGAAGGCCGTCTTCGGCAAAATCGGCGGC
CAGGCCGGTGACTTGGGTGGTGAAGCCCTGGAGAGGTATGTGGTCATCCGTCATTACCCC
ATCTCTTGTCTGTCTGTGACTCCATCCCATCTGCCCCCATACTCTCCCCATCCATAACTG
TCCCTGTTCTATGTGGCCCTGGCTCTGTCTCATCTGTCCCCAACTGTCCCTGATTGCCTC
TGTCCCCCAGGTTGTTCATCACCTACCCCCAGACCAAGACCTACTTCCCCCACTTCGACC
TGTCACATGGCTCCGCTCAGATCAAGGGGCACGGCAAGAAGGTGGCGGAGGCACTGGTTG
AGGCTGCCAACCACATCGATGACATCGCTGGTGCCCTCTCCAAGCTGAGCGACCTCCACG
CCCAAAAGCTCCGTGTGGACCCCGTCAACTTCAAAGTGAGCATCTGGGAAGGGGTGACCA
GTCTGGCTCCCCTCCTGCACACACCTCTGGCTACCCCCTCACCTCACCCCCTTGCTCACC
ATCTCCTTTTGCCTTTCAGCTGCTGGGTCACTGCTTCCTGGTGGTCGTGGCCGTCCACTT
CCCCTCTCTCCTGACCCCGGAGGTCCATGCTTCCCTGGACAAGTTCGTGTGTGCCGTGGG
CACCGTCCTTACTGCCAAGTACCGTTAA
• DNA sequences
7

Molecular biology data...
• Amino acid sequences
• Protein structure:
– X-ray crystallography
– NMR (Nuclear Magnetic
Resonance) Spectroscopy
8

Cell biology & proteomics data...
• Subcellular localization
9

Cell biology & proteomics data...
protein-protein
interactions
10

DNA microarray technology
Transcriptomics: DNA microarray
technology
11

Proteomics & transcriptomics data
Proteins encoded by periodically expressed
genes: a functionally diverse protein category
12

Phenotype data: human diseases
13

Jute Genome Sequencing
• Genome sequencing of jute (mystery of origin of
jute) disclosed by Bangladeshi Scientists, June
2010
• Opening up a new vista in the development of
variety of the world's most biodegradable natural
fibre
14

Abiotic Stress tolerance and
Crop Improvement
15

National Plant Genome Initiative (2009-2013)
1. Expand genomic resources for every major plant of
economic importance
• Understanding of plant epigenomes
• Mining plant diversity
• Survey sequence resources for thousands of plants
• A new kind of reference genome
• Integrated comparative sequence resources
2. Advance plant systems biology
• Toolkits to enable systems-level analysis of key plant processes
•Regulation of plant structure and composition
3. Translate basic discovery to the field
• High-throughput phenotyping under field conditions
• Breeding for improved local adaptation to biotic and
abiotic stress
• A National Genetic Trait Index

Ref: Shortliffe, 1995
Bioinformatics & Human Health
17

Bioinformatics as in-silico biology
- generates testable hypotheses for the biologist
- explores domains that can not be addressed
experimentally
Translational Bioinformatics / Medicine
18

Bioinformatics & Human Health
19

Would we want to live longer, healthier?
Would we benefit from better crops?
Bioinformatics
Why Bioinformatics?
20

Traditional Methods of
Drug Discovery
natural
(plant-derived)
treatment for
illness / ailments
↓
isolation of active
compound
(small, organic)
21

synthesis
of compound
↓
manipulation of
structure to get
better drug
(greater efficacy,
fewer side effects)
Aspirin
Traditional Methods of
Drug Discovery
22

Modern Methods of Drug
Discovery
What’s different?
• Drug discovery process begins
with a disease (rather than a treatment)
• Use disease model to pinpoint
relevant genetic / biological
components (i.e. possible drug targets)
23

Modern Drug Discovery
disease → genetic / biological target
↓
discovery of a “lead” molecule
- design assay to measure function of
target
- use assay to look for modulators of
target’s function
↓
high throughput screen (HTS)
- to identify “hits” (compounds with
binding in low nM to low μM range)
24

small molecule hits
↓
manipulate structure to increase potency
i.e. decrease Ki to low nM affinity
↓
*optimization of lead molecule into candidate drug*
fulfillment of required pharmacological properties:
potency, absorption, bioavailability, metabolism, safety
↓
clinical trials
Modern Drug Discovery
25

Interesting facts...
• Over 90% of drugs
entering clinical
trials fail to make it
to market
• The average cost
to bring a new
drug to market is
estimated at $770
million
26

Drug discovery and
development
• It costs in Billions USD and takes ~ 11 years
• In 2010, to bring a new Drug to Market was USD 1.2
Billion
• 4 out of 5 drugs fails during 1st Phase of Clinical trials
In-silico methods
• save an average of $130 million and 0.8 years per
drug (2003)
27

Beowulf Cluster
Computing
Each Computer in the cluster is equipped with:
– Intel Core 2 Duo 6400 Processor(Master: Core 2 Duo
6700)
– 2 Gigabytes of DDR RAM in Dual Channel
– D-Link Gigabyte Network Interface Card(Master: 2x
Cards)
– 60 Gigabyte Hard Drive(Master: 1000 Gigabyte RAID
5)
Sample Cluster Computer
CLUSTER USES: Clusters have a variety of different applications in the
world. They are used in bioinformatics to run DNA string matching algorithms or
to run protein folding applications. Geologists also use clusters to emulate and
predict earthquakes and model the interior of the Earth and sea floor Clusters
are even used to render and manipulate high-resolution graphics in engineering.
Our completed Beowulf cluster will use a computer algorithm known as BLAST,
(Basic Local Alignment Search Tool), to analyze massive sets of DNA sequences
for research into Bioinformatics.
Researcher: Ben Case
Researcher: Stephen
Ciesla
Advisor: Ed Harcout
Biology Consultant:
Lorraine Olendzenski
Node Computers
Master Computer
PROJECT: We constructed a parallel processing computer system using the Beowulf
cluster computing design created at NASA in an attempt to build a powerful computer that
could assist in Bioinformatics research and data analysis.
BEOWULF CLUSTERS: A Beowulf Cluster is a computer design that uses
parallel processing across multiple computers to create cheap and powerful
supercomputers. A Beowulf Cluster in practice is usually a collection of generic computers,
either stock systems or wholesale parts purchased independently and assembled,
connected through an internal network.
A cluster has two types of computers, a master computer, and node
computers. When a large problem or set of data is given to a Beowulf cluster, the master
computer first runs a program that breaks the problem into small discrete pieces; it then
sends a piece to each node to compute. As nodes finish their tasks, the master computer
continually sends more pieces to them until the entire problem has been computed.
MPICH2: In order for the master and node computers to communicate, some sort
message passing control structure is required. MPI,(Message Passing Interface) is the
most commonly used such control, and the one that we've incorporated into our project.
MPICH2 is a implementation of MPI that was specifically designed for use with cluster
computing systems and parallel processing. It is an open source set of libraries for various
high level programming languages that give programmers tools to easily control how large
problems are broken apart and distributed to the various computers in a cluster.
OUR CLUSTER: Using funding from the Biology department, the cluster we
constructed contains eight computers with one master and seven node computers. Each
computer in the cluster contains a dual core processor, giving us a total of 16 processors
to utilize. Each runs on the Fedora Core 6 version of Linux and uses the MPICH2 libraries
for message passing. They are all connected on a internal network through a high speed
gigabyte switch.
2 GB
RAM
SATA Hard Drives
D-Link NetworkIntel Core 2
RESULTS: The total processing power of our cluster has yet to be
determined. Once the cluster has been completely streamlined and stabilized,
we will run benchmark tests to calculate its average and peak performances
CLUSTER LAYOUT AND DESIGN:
28

Learning Life through Bioinformatics…Expertiselevel
SYS ALGO STAT VERB LUCKBIO
apprentice ~ 2,000 hours
mastery ~ 10,000 hours
critical weakness – below freshman level knowledge
Let’s ALL try to be Bioinformaticians!
29

SYS
ALGO
STAT
VERB
LUCK
(Serendipity)
BIO
SYStems: ability to identify,
understand, run, troubleshoot
existing bioinformatics tools
and techniques. (near
mastery skill needed ASAP)
ALGOrithms: ability to
create a new algorithm or
to implement these as a
software tool. (near
freshman skill needed to
start)
STATistics: ability to
identify proper statistical
method and to devise a
new statistical approach
to extract knowledge
from data. (above
apprentice skill
needed ASAP)
BIOlogy: ability to interpret
bioinformatics results in the proper
biological context. (well above
apprentice skill needed ASAP)
VERBal: ability to understand the
needs of individuals from diverse
backgrounds and ability to
communicate with them with their
discipline language. (near
mastery skill needed ASAP)
LUCK: ability to be in the right
place at the right time and have
the skill to work on unexpected
tasks. (CHANCE favors ONLY
the Prepared Minds !!!)
30

Five websites that all
Bioinformaticians should know
• NCBI (The National Center for Biotechnology Information)
– http://www.ncbi.nlm.nih.gov/
• EBI (The European Bioinformatics Institute)
– http://www.ebi.ac.uk/
• The Canadian Bioinformatics Resource
– http://www.cbr.nrc.ca/
• SwissProt/ExPASy (Swiss Bioinformatics Resource)
– http://expasy.cbr.nrc.ca/sprot/
• PDB (The Protein Databank)
– http://www.rcsb.org/PDB/
31

• First:
– Fix your Critical weakness.
• Second:
– Where should you invest next?
• To strengthen your stronger skills? … Or …
• To improve on your weaker skills?
• Answer ???
Continued…….
32

 Invest into what you are already good at!
 People with complementary skill-sets are
more valuable
 Differentiate yourself
 Pick a paper that interests you and redo
it!
 Compute the same quantities for a different
genome/annotations
Strengthen Your Stronger Skills
33

So… what is Bio-Bio-1?
• A TEAM with Passion for Learning Life through
Bioinformatics Knowledge and Skills…
• A TEAM with BIG Dreams to help flourishing the
Bioinformatics discipline in Bangladesh and in the
World…
• A voluntary not-for-profit organization, formed by some
passionate individuals in the late 2008 to learn
Bioinformatics for making some senses from the enigma
of life.
• Aims to spread the R&D excitement by infecting the
young individuals through several programs (weekly
study circles, workshops, etc)
34

Bio-Bio-1 Main Objectives
• Learn Bioinformatics from closely interacting multiple
academic and professional disciplines, including:
– Life Sciences, Computing Sciences, Mathematics, Statistics,
Software Engineering, High Performance Computing and Large
Scale Database optimization
• Popularize and spread the need for Bioinformatics
learning among the local students and professionals in
Bangladesh.
• Procure offshore sourcing programming and
development projects in Bioinformatics from abroad.
• Write practical handbooks in Bioinformatics and publish
papers in reputed journals.
35

Bio-Bio-1 Current Main Activities
• Organizing regular weekly Bioinformatics Study Circle
– Every Saturday at KAL Gallery, Dept. of Biochemistry and
Molecular Biology, University of Dhaka.
• Organizing Hands-On Bioinformatics Boot Camps &
Workshops.
• Collaboratively working with Microbial Genetics and
Bioinformatics Lab, Dept. of Microbiology, University of
Dhaka for the projects:
– “FMDV vaccine design and development” with Prof. Dr. Anwar
Hossain.
– and with Prof. Dr. Mojammel Hoque, to identify the factors that
increase the productivity and enzyme activity of protease and
keratinase of Bacillus Licheniformis.
36

• Zohirul Alam Tiemoon
– Founder and General Manager, Bio-Bio-1
Consultant, BASIS (www.basis.org.bd), Dhaka.
– Leading the Bio-Bio-1 v3.0 with new vigor!
• Saddam Hossain
– Founding Core Member and Chief Researcher, Bio-Bio-1. Head,
Business Intelligence, Airtel Bangladesh
– Re-incarnated Bio-Bio-1 from long hibernation! Leading the R&D
Projects both in Bio-Bio-1 v2.0 and v3.0!
• Farjana Khatun
– Founding Core Member and Coordinator, Bio-Bio-1. Lecturer,
Department of Pharmacy, East West University
– The Pioneer Biology knowledge provider in Bio-Bio-1. Patient
and Persistent Coordinator!
37
Bio-Bio-1 Prime Movers (& Shakers) 

Bio-Bio-1 Prime Movers (& Shakers) 
• Mosharraf Hossain
– Core Member and Coordinator, Bio-Bio-1. Head, Operations
Support System & Business Support System, Novo Tel Ltd.
– Passionate Mentor for the Bio-Bio-1 Study Circle Participants!
• Arafat Rahman
– Core Member and Researcher, Bio-Bio-1. Research Student,
Microbial Genetics and Bioinformatics Lab, Dept. of
Microbiology, University of Dhaka.
– Great Analytical Mind with knowledge and interest in diverse
scientific disciplines! Still a great Bio-Bio-1 Anchor!
• Arif Ashraf Opu
– Core Member and Researcher, Bio-Bio-1. Research Student,
Plant Biotechnology Lab, University of Dhaka
– Great Out-of-the-Box Thinker with lucid Presentation Skills!
38

Credits / Acknowledgments
• www.cbs.dtu.dk/phdcourse/cookbooks/What_is_bioin
• Prof. Zeba Islam Seraj, Professor, Dept of
Biochemistry and Molecular Biology, Dhaka University
• Prof. Supten Sarbadhikary, India - Chair, HL7 India,
Visiting Professor, Dept of Health
Informatics, Bangladesh University of Health Sciences
• The Bio-Bio-1 CORE TEAM
• The Google & The WWW
39

Thank You very much
for all your time and patience 
Hope You will enjoy this 2-days workshop in
UODA!

Bioinformatics n bio-bio-1_uoda_workshop_4_july_2013_v1.0

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