This document discusses the field of computational biology and its potential future applications in pharmaceutical research. It begins by defining computational biology as the use of biological data and algorithms to study biological systems. The document then outlines several subfields of computational biology, including computational bio-modeling, genomics, neuroscience, evolutionary biology, and cancer biology. It notes that computational biology has helped with efforts like genome sequencing and brain modeling. The document concludes by suggesting that as pharmaceutical companies face challenges developing new drugs, computational biologists may play a larger role in drug discovery by analyzing large datasets to find new treatment signals.

1. COMPUTATIONAL BIOLOGISTS –
THE NEXT PHARMA SCIENTISTS ?
Presented by :
DEBARATI ROY
Roll No-20101912020
Reg No-122010210020
BCDA College of Pharmacy & Technology,
Kolkata--700127
Under Guideence of:
SURAJIT GOON,ASSISTANT PROFESSOR
BCDA COLLEGE OF PHARMACY &
TECHNOLOGY,
KOLKATA-700127

2. What is Computational Biology ?
Prior to the advent of Computational Biology
Impact of Computational Biology
Big-Data in Computational Biology
The Sub-fields of Computational Biology :
1. Computational Bio-Modeling
2. Computational Genomics
3. Computational Neurosciences
4. Computational Evolutionary biology
5. Cancer computational biology
Future scope and impact
KEY FEATURES OF THE SEMINAR

3.  Computational Biology is also known
as bioinformatics it began to develop in
the early 1970s
 In this field biological data is used to
develop algorithms and relations among
various biological systems
 The various subfields include
computational bio-modeling,
computational genomics, computational
neuroscience, computational
pharmacology, computational
evolutionary biology and cancer
computational biology
WHAT IS COMPUTATIONAL BIOLOGY ?

4.  Computational bio-modeling is
concerned with
building computer models of
biological systems.
COMPUTATIONAL BIO-MODELING

5.  Computational genomics also
known as Computational and
Statistical Genetics is a field
within genomics which
studies the genomes of cells
and organisms.
 The Human Genome
Project is an example of
computational genomics.
 Once fully implemented, this could allow for doctors to analyze the genome of an
individual patient. This opens the possibility of personalized medicine, prescribing
treatments based on a patient’s pre-existing genetic patterns.
COMPUTATIONAL GENOMICS

6.  Various types of models of the brain have been created which include :
1. Realistic Brain Models
2. Simplifying Brain
 Computational
neuroscience is the
study of brain function
in terms of the
information processing
properties of the
structures that make up
the nervous system.
COMPUTATIONAL NEUROSCIENCES

7.  Computational biology has
assisted the field of
evolutionary biology in many
capacities which includes
using DNA data to evaluate
the evolutionary change of a
species over time.
COMPUTATIONAL EVOLUTIONARY BIOLOGY

8.  Cancer
computational
biology is a field
that aims to
determine the
future mutations
in cancer through
an algorithmic
approach to
analyzing data.
CANCER COMPUTATIONAL BIOLOGY

9.  Researchers were unable to share
biological information interpreted
from various analytical methods
and biological experiments
 Research in areas like artificial
intelligence was using network
models of the human brain instead
of real biological data collected via
EEG.
PRIOR TO THE ADVENT OF COMPUTATIONAL BIOLOGY

10.  By the 20th century information was being shared among researchers through the use of
punch cards
 With the use of punch cards The amount of data being shared began to grow
exponentially.
 This required the development of new computational methods in order to quickly analyze
and interpret relevant information.
 Computational biology has been used to help sequence the human genome, create
accurate models of the human brain, and assist in modeling biological systems.
IMPACT OF COMPUTATIONAL BIOLOGY

11. IMPACT OF COMPUTATIONAL BIOLOGY

12.  Conventionally biologists used Excel but we have now exceeded the Excel barrier in
terms of the number of rows and columns and the computational powers of Excel.
IMPACT OF COMPUTATIONAL BIOLOGY

13. BIG-DATA IN COMPUTATIONAL BIOLOGY

14.  Computational biology was not in the spotlight earlier as pharmaceutical
companies were not facing the kinds of problems that are best-suited to
computational biologists which include finding useful signals in
tremendously large sets of unsorted and noisy data.
 As the pharmaceutical industry's best selling drugs fall off the markets
there are a few drugs in the pipeline to replace them and hence there are
signs that big-pharma could turn more of its attention to biologically
derived medicines.
 If that happens, computational biologists will likely play a leading role in
the discovery of new drugs.
 In the United States of America, The Big Data Research and Development
Initiative pledges $200 million for NIH, the National Science Foundation to
support data collection, analysis, and dispersion of biological data.
FUTURE SCOPE AND IMPACT

15. Francis Collins
Director, NIH, USA
‘If I were a senior or first-year graduate student interested in biology, I would migrate as
fast as I could into the field of computational biology, There are vast quantities of high-
quality data accessible to anybody who has the skills to find the nuggets of truth that are
hiding in that information.’
FUTURE SCOPE AND IMPACT

16. REFERENCES
• International Society for Computational Biology-website
• Introduction of computational Biology-an evalutional approach by
Bernhard Haubold,Thomas wiehe
• Models and algorithms for Genome evaluation by Chauve,cedric,EI
Mabrouk,Nadia,Tannier,Eric
• Computational Biology by Dress,A.,Linial,M.,Troyanskaya,o.,Vingron,M.