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Tuesday, December 4, 2012

Important fields in bioinformatics / Branches of Bioinformatics

These are some of the important fields in bioinformatics

1. Structural Bioinformatics:

Predicting the 3D structure of a protein from its protein sequence. Homology modelling is the best method for predicting the protein structures by using already structured or crystallized protein as a template.

2. Drug Designing:

Drug design is the approach of finding drugs by design, based on their biological targets. Typically a drug target is a key molecule involved in a particular metabolic or signalling pathway that is specific to a disease condition or pathology, or to the infectivity or survival of a microbial pathogen.
Computer-assisted drug design uses computational chemistry to discover, enhance, or study drugs and related biologically active molecules.

3. Phylogenetics:

Predicting the genetic or evolutionary relation of set of organisms. Mitochondrial SNPs and Microsatellites ( DNA repeats) are mostly used in Phylogenetics. MEGA,PAUP are PAUP* are some of the important softwares. Maximum Parsimony and Maximum Likelyhood are mostly used methods.

4. Computational biology:

Computational biology is an interdisciplinary field that applies the techniques of computer science, applied mathematics, and statistics to address problems inspired by biology.

5. Population Genetics:

Population Genetics is a study of genotype frequency distribution and the change in the genotype frequencies under the influence of Natural selection, genetics drift, mutation and gene flow. Coalescent theory is one of the most used theory to predict the most recent ancester. Arlequin is one of the best and most used software in population gentics.

6. Genotype Analysis:

Genotype = Genetic variation, SNP,Mutation ....

1. Studying Genotype and phenotype association.
2. Studying Genotype frequencies. There is no specific software for genotype analysis. But its called the "Generation Next Market using Bioinformatics....". Genotyping is mostly done using Illumina and Affy microarry chips.

7. Splicing Site prediction:

Splicing prediction is a very important application of Bioinformatics which is very important in Gene expression studies. Visit also Alternative Splicing site Predictior.

8. MiRNA prediction:

MiRNA = MicroRNA. MiRNA emerged as a new Gene regulatory element and gained more space in research. 20 -23 base pair RNA which regulates a gene or genes. So many methods and softwares have been developed to predicting this tiny RNAs. But still they are not precise in predicting. It means that we need some more information from experimental labs to predict.

MiRNA binds to the gene and regulates the gene. Most of the time it down regulate the gene expression. Predicting the MiRNA target is also a very important problem in Bioinformatics.

miRNA Registry from Sanger Institute.

MiRNA target prediction software

There are so many softwares for miRNA and Target prediction....

9. RNA Structure prediction:

The functional form of single stranded RNA molecules frequently requires a specific tertiary structure. The scaffold for this structure is provided by secondary structural elements which are hydrogen bonds within the molecule. This leads to several recognizable "domains" of secondary structure like hairpin loops, bulges and internal loops. There has been a significant amount of bioinformatics research directed at the RNA structure prediction problem.

10. Gene Prediction:

Predicting the Gene by the predefined conditions. Comparative genomics is the best method for predicting the gene.

Some of the softwares..

GeneMark, Genscan

11. Transcription factor binding site prediction:

Predicting the transcription factor. Most common method is to use "Comparative genomics". And finding clusters of motifs in the noncoding part of gene.

12. Genome Annotation:

Predicitng the genes, coding and noncoding sequences are called genome annotation.
Most of the people follow comparative genomics to annotate the newly sequenced genomes.

GOLD is the database for ongoing genome projects.

13. Ancestry Prediction:

Predicting the Ancestry of an individual based on his/her genetic signatures or SNPs.
mitochondrial SNPs are used in predicting Maternal ancestry because Mitochondria is passed ONLY through mother to the child.
Y chromosome SNPs are used in predicting paternal ancestry becuase Y chromsome is passed from Father to the child.
Ancestry is one of the successful field in Bioinformatics. Genography project by Dr. Spencer Wells is one of the finest one.

14. Mathematical Modelling:

Using mathemetics to predict the out come of some complex real time problems which cannot be done in lab or in reality. Ex: population dynamics.

15. Ethnicity Prediction:

Predicting the ethnicity of an individual by using genetics variations. Each ethnicity is defined by a set of genetic variations.

16. Functional Domains prediction:

Predicting the protein domains which are functionally important from its protein sequence like active sites in a protein.

17. Motif Prediction /Pattern matching:

Predicting the motifs or motif clusters which are functionaly important.
Ex: regulatory motifs, Binding site motifs ...miRNA motics ..repeat motis ...Microsatellites are also a kind of motifs.

18. Protein - protein interaction :

Protein–protein interactions occur when two or more proteins bind together, often to carry out their biological function. Many of the most important molecular processes in the cell such as DNA replication are carried out by large molecular machines that are built from a large number of protein components organized by their protein–protein interactions. Protein interactions have been studied from the perspectives of biochemistry, quantum chemistry, molecular dynamics, chemical biology, signal transduction and other metabolic or genetic/epigenetic networks. Indeed, protein–protein interactions are at the core of the entire interactomics system of any living cell.

19. Protein folding

One of the famous and most important and still unsolved problem.

20. Database development:

In some sense Bioinformatics is called as "Comparative Method". Because Bioinformatics depends on Databases for all of its analysis. So developing data base is a very important project. Many companies surviving by devloping and updating the databases.

NCBI , PDB and UCSC genome browser are some of the very important databases.

21. Software development:

Incorporating the usage of Softwares in Biological analysis is called "Bioinformatics".

22. Developing Bioinformatics Methods/Approaches 

23. Primer designing


 One of the most important factors in successful automated DNA sequencing is proper primer design.
24. Modeling genetics History
25. Ancient DNA
26. Population Genetics Simulations
27. Finding SNPs
28. Genome wide Association Studies
29. Systems Biology

Systems biology is a biology-based inter-disciplinary field of study that focuses on complex interactions within biological systems, using a more holistic perspective  approach to biological and biomedical research.

30. Homology Search

(1) A degree of similarity, as in position or structure, and that may indicate a common origin; a correspondence of structure
(2) (evolutionary biology) A state of similarity in structure and anatomical position but not necessarily in function between different organisms indicating a common ancestry or evolutionary origin
(3) (genetics) A condition denoting to the pair of chromosomes having corresponding genes for a particular trait or characteristic

31. Computational Genomics

Computational genomics is the study of deciphering biology from genome sequences using computational analysis, including both DNA and RNA.

1 comment:

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