EDU TECHNO FRIEND
Wednesday 27 December 2017
Saturday 18 November 2017
Saturday 11 November 2017
Thursday 28 September 2017
Friday 15 September 2017
BIOINFORMATICS
Bioinformatics is
an interdisciplinary field that develops methods and software
tools for
understanding biological data.
As an interdisciplinary field of science, bioinformatics
combines computer
science, statistics, mathematics, and engineering to analyze and interpret biological data. Bioinformatics has been used
for in silico analyses of biological queries using mathematical and statistical techniques.
Bioinformatics
is both an umbrella
term for
the body of biological studies that use computer programming as part of their methodology, as well
as a reference to specific analysis "pipelines" that are repeatedly
used, particularly in the field of genomics. Common uses of bioinformatics include the
identification of candidate genes and single nucleotide polymorphisms (SNPs). Often, such identification is made with
the aim of better understanding the genetic basis of disease, unique
adaptations, desirable properties or differences between populations. In a less
formal way, bioinformatics also tries to understand the organizational
principles within nucleic
acid and protein sequences, called proteomics.
Bioinformatics
has become an important part of many areas of biology. In experimental molecular
biology,
bioinformatics techniques such as image and signal
processing allow
extraction of useful results from large amounts of raw data. In the field of
genetics and genomics, it aids in sequencing and annotating genomes and their
observed mutations. It
plays a role in the text
mining of
biological literature and the development of biological and gene ontologies to organize and query biological data.
It also plays a role in the analysis of gene and protein expression and
regulation. Bioinformatics tools aid in the comparison of genetic and genomic
data and more generally in the understanding of evolutionary aspects of
molecular biology. At a more integrative level, it helps analyze and catalogue
the biological pathways and networks that are an important part of systems
biology
Education
for Bioinformatics
Education in
bioinformatics has undergone a sea change, from informal workshops and training
courses to structured certificate, diploma, and degree programs—spanning casual
self-enriching courses all the way to doctorate programs. The evolution of
curriculum, instructional methodologies, and initiatives supporting the
dissemination of bioinformatics is presented here. Building on the early applications of
informatics (computer science) to the field of biology, bioinformatics research
entails input from the diverse disciplines of mathematics and statistics,
physics and chemistry, and medicine and pharmacology. Providing education in
bioinformatics is challenging from this multidisciplinary perspective, and
represents short- and long-term efforts directed at casual and dedicated
learners in academic and industrial environments.
Bioinformatics is
a rapidly growing career field and an emerging scientific discipline. This
course focuses on employing existing bioinformatic resources - mainly web-based
programs and databases - to access the wealth of data to answer questions
relevant to the average biologist, and is highly hands-on. There are different
types of career opportunities available for different stream students,
Scientific Curator, Gene Analyst, Protein Analyst, Phylogenitist, Research
Scientist / Associate, Data base programmer, Bioinformatics software developer,
Computational biologist, Network Administrator / Analyst, Structural analyst,
Molecular Modeler, Bio-statistician, Bio-mechanics, Database programmer,
Cheminformatician, Pharmacogenetician, Pharmacogenomics, Research Scientist /
Associate.
Objectives of
Teaching Bioinformatics
After learning the
concepts of bioinformatics, the student will be able to:
1.
Describe the key biochemistry and molecular concepts that are relevant
to bioinformatics analyses
2.
Apply online resources and databases to gain access to sequence data
and literature information
3.
Analyze using pairwise sequence alignment
4.
Interpret the results from BLAST
5.
Compare a query sequence against an online database using BLAST
6.
Describe basic principles for multiple sequence alignment
7.
Analyze using online programs for multiple sequence alignment
8.
Describe the key concepts for molecular evolution and molecular
phylogeny
9.
Explain the major steps and methods for phylogenetic analysis
10. Analyze using the major
bioinformatics approaches to RNA analyses
11. Describe the basic
principles of key bioinformatics strategies for genome-wide gene expression
analyses
12. Demonstrate the key concepts
for proteins and major bioinformatics tools for high-throughput protein
analysis
13. Analyze using the main approaches
to protein structure bioinformatics analysis
14. Demonstrate the major
strategies for functional genomics analyses
15. Describe the major
strategies for genome sequencing analyses
16. Apply online database for
access to human disease information
17. Analyze using key
bioinformatics approaches to human disease research
Friday 1 September 2017
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