Introduction to Bioinformatics to Computer Scientists

http://www.cs.indiana.edu/~predrag/files/cohen_2004.pdf

Data Mining for Computer Scientists

http://arxiv.org/ftp/arxiv/papers/1205/1205.1125.pdf

Introduction:-

What is bioinformatics

Bioinformatics is the application of computer technology to the management of biological information. Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development. The need for Bioinformatics capabilities has been precipitated by the explosion of publicly available genomic information resulting from the Human Genome Project.

The goal of this project – determination of the sequence of the entire human genome (approximately three billion base pairs) – will be reached by the year 2020. The science of Bioinformatics, which is the melding of molecular biology with computer science, is essential to the use of genomic information in understanding human diseases and in the identification of new molecular targets for drug discovery.

In recognition of this, many universities, government institutions and pharmaceutical firms have formed bioinformatics groups, consisting of computational biologists and bioinformatics computer scientists. Such groups will be key to unraveling the mass of information generated by large scale sequencing efforts underway in laboratories around the world.

http://www.statru.org/wp-content/uploads/2012/04/01_Statistical-Methods-in-Bioinformatics.pdf

Introduction:

The significance of any genetic or biological implication based on dna sequencing depends on its accuracy. The statistical evaluation of accuracy requires a probabilistic model of measurement error.Here, we describe two statistical models of sequence assembly from shotgun sequencing respectively for the cases of haploid and diploid genome. The first model allows us to convert quality scores into probabilities. it combines quality scores of base calling and the power of alignment to improve sequencing accuracy. Specifically, we represent probabilistic errors by logistical models that takes quality scores and other genomic features as covariates. since the true sequence is unknown , an Em algorithm is used to deal with missing data. The second model describes the case in which Dna reads are from one diploid genome. The statistical model consists of sequencing errors, compositional information and haplotype memberships of dna fragment. Consequently, optimal haplotype sequences can be inferred by maximising the probability among all configurations conditional on the given assembly. In the meantime, this probability, together with the coverage information, provides an assessment of the confidence for the reconstruction.

www.ohio.edu/people/just/TALKS/Wyatt.ppt 

http://www.ibis.org.ir/files/site1/books/mathematics_of_bioinformatics.pdf

Introduction: Bioinformatics is conceptualising biology in terms of molecules (in the sense of physical chemistry) and applying "informatics techniques" (derived from disciplines such as applied maths, computer science and statistics) to understand and organise the information associated with these molecules, on a large scale. In short, bioinformatics is a management information system for molecular biology and has many practical applicationsMath can be used to understand life from the molecular to the biosphere level - the origin and evolution of organisms, - the nature of the genomic blueprints - the universal genetic code - ecological relationships.Math helps us look for trends, patterns and relationships that may or may not be obvious to scientists.Math allows us to describe the dimensions of genes, sizes of organelles, cells organs and whole organisms cells, organs and whole organisms

Here is a video explainer:

Here is a video explainer:

significant similarity to a given query sequence

For eg, the concept of Mendel's law of inheritance:-

Here is an example:-

The image schematic showing the flow of data mining in bioinformatics were taken from BioInformatics Institute of India: http://image.slidesharecdn.com/bioinformatics-090429002240-phpapp02/95/bioinformatics-36-638.jpg?cb=1427754692

The video explaining genome annotation was taken from

http://www.youtube.com/watch?v=on4TMnuYTaU

The video explaining sequence analysis was taken from http://www.youtube.com/watch?v=Z72nvSUtEng

The video explainer of the Human Genome Project was taken from http://www.youtube.com/watch?v=ifMkMsq3pGs

The poster of the Human Genome Project was taken at

http://www.abpischools.org.uk/page/modules/hgenome/index.cfm

The schematic logo of the Human Genome Project was taken from http://www.knowledgene.com/Image61.gif

• Do you think that the field of Bio Informatics is relevant today?
• What are the roles of Mathematics,Statistics and Computing in Bioinformatics?
• Do you think Bio Informatics will directly affect you in your day-to-day activities?
• Will advances in Bio Informatics result in a big difference/impact in your current lifestyle?
• Do you think that Bio Informatics will be an effective tool for Disease Diagnosis?
• Will Bio Informatics be used to enhance human abilities(like physical and mental strength) in your opinion?
• Do you think that the Human Genome Project is a very useful undertaking?
• Will you approve getting your DNA sequenced(from privacy and medical points of view)?
• Do you believe that Bio Informatics is the way forward for human progress?
• 
  

The image explainer of Biological networks was taken from https://imdevsoftware.files.wordpress.com/2013/04/bionetwork1.png

The image illustrating concept of Mendel's law was taken from

http://media.web.britannica.com/eb-media/75/775-004-F3BAFB88.gif

The links mentioned below feature videos explaining the application of discrete mathematics in bioinformatics.

www.youtube.com/watch?v=hSld-Cf-3oQ

https://www.youtube.com/watch?v=immUv5c8ieU

Gene expression: Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product. These products are often proteins, but in non-protein coding genes such as transfer RNA (tRNA) or small nuclear RNA (snRNA) genes, the product is a functional RNA.

Phylogenetic tree:A phylogenetic tree or evolutionary tree is a branching diagram or "tree" showing the inferred evolutionary relationships among various biological species or other entities—their phylogeny—based upon similarities and differences in their physical or genetic characteristics.

Context-free grammar:In formal language theory, a context-free grammar (CFG) is a formal grammar in which every production rule is of the form V → w

where V is a single nonterminal symbol, and w is a string of terminals and/or nonterminals (w can be empty). A formal grammar is considered "context free" when its production rules can be applied regardless of the context of a nonterminal.

Terminal and non-terminal symbols: In computer science, terminal and non-terminal symbols are the lexical elements used in specifying the production rules constituting a formal grammar. Terminal symbols are the elementary symbols of the language defined by a formal grammar.

Percent identity: Percent identity refers to a quantitative measurement of the similarity between two sequences (DNA, amino acid or otherwise)

Mathematical Knot: A mathematician's knot differs from the regular in that the ends are joined together so that it cannot be undone.In mathematical language, a knot is an embedding of a circle in 3-dimensional space.

Composite knot:A knot that can be expressed as the composition of two nontrivial knots is called a composite knot.

Linking number: This is a topological property that determines the degree of supercoiling. It defi nes the number of times a strand of DNA winds in the right - handed direction around the helix axis when the axis is constrained to lie in a plane

Supercoiling: Supercoiling is an abstract mathematical property representing the sum of twist and writhe. The twist is the number of helical turns in the DNA and the writhe is the number of times the double helix crosses over on itself (these are the supercoils)

.

In the not too distant future, the potential for using genes themselves to treat disease may become a reality. Gene therapy is the approach used to treat, cure or even prevent disease by changing the expression of a persons genes. Currently, this field is in its infantile stage with clinical trials for many different types of cancer and other diseases ongoing.

With the specific details of the genetic mechanisms of diseases being unravelled, the development of diagnostic tests to measure a persons susceptibility to different diseases may become a distinct reality. Preventative actions such as change of lifestyle or having treatment at the earliest possible stages when they are more likely to be successful, could result in huge advances in our struggle to conquer disease.

In probability theory, a stochastic process, or often random process, is a collection of random variables, representing the evolution of some system of random values over time.

Phylogenetic tree estimation

A phylogenetic tree or evolutionary tree is a branching diagram or "tree" showing the inferred evolutionary relationships among various biological species or other entities—their phylogeny—based upon similarities and differences in their physical or genetic characteristics.

Bayesian Statistics

Bayesian statistics is a system for describing epistemological uncertainty using the mathematical language of probability. In the 'Bayesian paradigm,' degrees of belief in states of nature are specified; these are non-negative, and the total belief in all states of nature is fixed to be one.

PAM Substitution Matrix

A PAM matrix is a matrix where each column and row represents one of the twenty standard amino acids. In bioinformatics, PAM matrices are regularly used as substitution matrices to score sequence alignment for proteins.

Markov Model

In probability theory, a Markov model is  used to model randomly changing systems where it is assumed that future states depend only on the present state and not on the sequence of events that preceded it.Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable.

1) http://www.powershow.com/view1/24a535-ZDc1Z/Computational_Statistics_with_Application_to_Bioinformatics_powerpoint_ppt_presentation 2) http://www.powershow.com/view1/233fd6-ZDc1Z/Bayesian_Statistics_for_Bioinformatics_powerpoint_ppt_presentation Books and Journals 1) http://chagall.med.cornell.edu/BioinfoCourse/PDFs/Lecture3/bioinformatics_tutorial.pdf 2) https://cran.r-project.org/doc/contrib/Seefeld_StatsRBio.pdf 3) http://iase-web.org/documents/papers/icots7/5D2_ARHI.pdf Videos 1) www.youtube.com/watch?v=p_REiNh2DWw 2) www.youtube.com/watch?v=YL8Lys3t-hQ

How will it help in molecular medicine?

The completion of the human genome means that we can search for the genes directly associated with different diseases and begin to understand the molecular basis of these diseases more clearly. This new knowledge of the molecular mechanisms of disease will enable better treatments, cures and even preventative tests to be developed.

How will it help in personalized medicine?

Potentially life saving drugs never make it to the marketplace. Today, doctors have to use trial and error to find the best drug to treat a particular patient as those with the same clinical symptoms can show a wide range of responses to the same treatment. In the future,with personalized medicine coming into play, doctors will be able to analyse a patient's genetic profile and prescribe the best available drug therapy and dosage from the beginning which can prove helpful in many life-or-death situations also.

Does it help in preventive medicine?

Keeping in mind the adage "Prevention is better than cure" with the help of bioinformatics one can follow this to the best possible extent.

With the specific details of the genetic mechanisms o diseases being unravelled, the development of diagnostic tests to measure a persons susceptibility to different diseases may become a distinct reality. Preventative actions such as change of lifestyle or having treatment at the earliest possible stages when they are more likely to be successful, could result in huge advances in our struggle to conquer disease.

With the specific details of the genetic mechanisms of diseases being unravelled, the development of diagnostic tests to measure a persons susceptibility to different diseases may become a distinct reality. Preventative actions such as change of lifestyle or having treatment at the earliest possible stages when they are more likely to be successful, could result in huge advances in our struggle to conquer disease.

In what way it help in drug development?

Using computational tools to identify and validate new drug targets, more specific medicines that act on the cause, not merely the symptoms, of the disease can be developed. These highly specific drugs promise to have fewer side effects than many of today's medicines.

The following article illustrates the contribution of mathematics in making bioinformatics education comprehensible.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3771232/

http://rce.csuchico.edu/sites/default/files/online/the_role_of_mathematics_stats_and_computer_science_in_bioinformatics_reduced.pdf

Here is a video about the introduction to Bioinformatics:

Here is a schematic explainer on bioinformatics: