importance of biostatics in modern reasearch
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This document discusses the role of biostatistics in modern research. It begins by defining statistics and biostatistics, noting that biostatistics is the application of statistical methods to biological problems. It then provides examples of how biostatistics is used across various fields, including community medicine, cancer research, pharmacology, ecology, demography, genetics, and more. Key applications mentioned include clinical trials and research, determining treatment efficacy, analyzing data from advanced technologies, and making inferences from genetic and population data.
importance of biostatics in modern reasearch
- 1. WELCOME
- 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.
- 18. THANK YOU