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WELCOME
B Y
S A S N A . P. S
ROLE OF BIOSTATISTICS IN
MODERN RESEARCH
Through the slides......
*Statistic and biostatistics
*Application of Biostatistics
-In Community medicine & public health
-In Cancer researches
-In Advanced biomedical technologies
-In Pharmacology
-In Ecology
-In Demography
-In Population genetics & statistical genetics
-In Bioinformatics
-In Systems biology
-In agriculture
-In genetics
-In physiology & anatomy
STATISTICS AND BIOSTATISTICS
Statistics
•collecting
• analysing
• interpreting and
• making inferences
Biostatistics/Biometry
•Application of statistics in biology
•Very useful in deigning of biological experiments
APPLICATIONS OF BIOSTATISTICS
1) COMMUNITY MEDICINE AND PUBLIC HEALTH
• Useful in determining if a treatment will work out or
not.
• To test usefulness of vaccines in epidemiological
studies.
• Medical research studies use Biostatistics from
beginning to end.
• To reach conclusions about diseases within certain
population groups .
• To determine development , progressive nature and
spread of a disease. I t predicts mortality rate,symptoms
and even the time of occurrence. Eg: Flu
• Another example is in case of development of polio
vaccine.
• Randomization—Paul Meier---experimental and
standard treatment comparison----calculate
efficiency of treatment.
2) IN CANCER RESEARCHES
Cancer is not a one size fits all disease . So it is used to
identify how factors such as drug interaction , association
between 2 attributes (smoking & cancer) diet etc.
Examine traits of cancer and occurrences in various ages ,
genders , and racial groups to work on prevention.
 Clinical trials—number based.
 Make predictions about real effects of treatment.
 Randomization and stratification techniques applied here
also.
3) IN ADVANCED BIOMEDICAL TECHNOLOGIES
 Computer intensive biostatistical methods–
bootstrapping and resampling methods.
 Micro arrays , next generation sequencers (for
genomics) , mass spectrometry (proteins)
The datas obtained from these method could be
analysed only with the help of biostatistical methods
(problem of multicolinearity)
Very difficult with classical statistical methods like
linear or logistic regression.
4) IN PHARMACOLOGY
• To find action of a drug.
• To compare actions of two different drugs and dosages
• To find relative potency of new drug .
5) IN ECOLOGY
 Constructing biological pyramids/ecological
pyramids—calculation of total energy content in different
trophic levels.
 Effects of climate change and other environmental
impacts on ecological communities.
6) IN DEMOGRAPHY
 Used in estimating the attributes of population—sex ratio ,
birth rate , density etc.
Used in drawing growth curves of a population at a given
time .Eg: Logistic growth curve.
7) IN POPULATION GENETICS & STATISTICAL
GENETICS
 Link variation in genotype with a variation in a phenotype.
 Study distributions and changes in allele frequency as
population is subject to Natural selection , Genetic drift ,
mutation and gene flow.
 Statistical genetics—development and application of
statistical methods for drawing inferences from genetic data.
 Biological geneticist tend to collaborate with lab geneticists
, molecular biologists , clinicians , & bioinformaticians.
8) IN BIOINFORMATICS
 In biological sequence analysis—assign function to
genes and proteins by the study of similarities between
the compared sequences.
9) IN SYSTEMS BIOLOGY
• In gene network inference or pathway analysis.
Systems biology is a biology based inter-disciplinary field
of study that focuses on complex interactions within
biological systems.
• It makes heavy use of mathematical and computational
models.
10) IN AGRICULTURE
* In crop improvement.
In agricultural works, the decision as to whether one
variety of crop is better than the other will be made on the
results of a carefully planned series of statistical
experiments.
11) IN GENETICS
Two important laws in genetics for example is largely
used in the field of genetics.
o Mendel's Laws
o Hardy- Weingberg equilibrium
12) IN PHYSIOLOGY AND ANATOMY
 Limits of normal and healthy values in a population.
 Differences between means and populations.
THANK YOU

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importance of biostatics in modern reasearch

  • 2. B Y S A S N A . P. S ROLE OF BIOSTATISTICS IN MODERN RESEARCH
  • 3. Through the slides...... *Statistic and biostatistics *Application of Biostatistics -In Community medicine & public health -In Cancer researches -In Advanced biomedical technologies -In Pharmacology -In Ecology -In Demography -In Population genetics & statistical genetics -In Bioinformatics -In Systems biology -In agriculture -In genetics -In physiology & anatomy
  • 4. STATISTICS AND BIOSTATISTICS Statistics •collecting • analysing • interpreting and • making inferences Biostatistics/Biometry •Application of statistics in biology •Very useful in deigning of biological experiments
  • 5. APPLICATIONS OF BIOSTATISTICS 1) COMMUNITY MEDICINE AND PUBLIC HEALTH • Useful in determining if a treatment will work out or not. • To test usefulness of vaccines in epidemiological studies. • Medical research studies use Biostatistics from beginning to end.
  • 6. • To reach conclusions about diseases within certain population groups . • To determine development , progressive nature and spread of a disease. I t predicts mortality rate,symptoms and even the time of occurrence. Eg: Flu • Another example is in case of development of polio vaccine. • Randomization—Paul Meier---experimental and standard treatment comparison----calculate efficiency of treatment.
  • 7. 2) IN CANCER RESEARCHES Cancer is not a one size fits all disease . So it is used to identify how factors such as drug interaction , association between 2 attributes (smoking & cancer) diet etc. Examine traits of cancer and occurrences in various ages , genders , and racial groups to work on prevention.  Clinical trials—number based.  Make predictions about real effects of treatment.  Randomization and stratification techniques applied here also.
  • 8. 3) IN ADVANCED BIOMEDICAL TECHNOLOGIES  Computer intensive biostatistical methods– bootstrapping and resampling methods.  Micro arrays , next generation sequencers (for genomics) , mass spectrometry (proteins) The datas obtained from these method could be analysed only with the help of biostatistical methods (problem of multicolinearity) Very difficult with classical statistical methods like linear or logistic regression.
  • 9. 4) IN PHARMACOLOGY • To find action of a drug. • To compare actions of two different drugs and dosages • To find relative potency of new drug .
  • 10. 5) IN ECOLOGY  Constructing biological pyramids/ecological pyramids—calculation of total energy content in different trophic levels.  Effects of climate change and other environmental impacts on ecological communities.
  • 11. 6) IN DEMOGRAPHY  Used in estimating the attributes of population—sex ratio , birth rate , density etc. Used in drawing growth curves of a population at a given time .Eg: Logistic growth curve.
  • 12. 7) IN POPULATION GENETICS & STATISTICAL GENETICS  Link variation in genotype with a variation in a phenotype.  Study distributions and changes in allele frequency as population is subject to Natural selection , Genetic drift , mutation and gene flow.  Statistical genetics—development and application of statistical methods for drawing inferences from genetic data.  Biological geneticist tend to collaborate with lab geneticists , molecular biologists , clinicians , & bioinformaticians.
  • 13. 8) IN BIOINFORMATICS  In biological sequence analysis—assign function to genes and proteins by the study of similarities between the compared sequences.
  • 14. 9) IN SYSTEMS BIOLOGY • In gene network inference or pathway analysis. Systems biology is a biology based inter-disciplinary field of study that focuses on complex interactions within biological systems. • It makes heavy use of mathematical and computational models.
  • 15. 10) IN AGRICULTURE * In crop improvement. In agricultural works, the decision as to whether one variety of crop is better than the other will be made on the results of a carefully planned series of statistical experiments.
  • 16. 11) IN GENETICS Two important laws in genetics for example is largely used in the field of genetics. o Mendel's Laws o Hardy- Weingberg equilibrium
  • 17. 12) IN PHYSIOLOGY AND ANATOMY  Limits of normal and healthy values in a population.  Differences between means and populations.