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Here is a short summary of the concepts that will be covered in this course module.

Computational genefinding using hidden markov models

The first problem we will study is the annotation of DNA sequences into regions of interest. Our focus is on finding genes that code for proteins. Our approach is to use available annotated DNA sequences to train sequential models, and then to use the trained model to label new DNA segments. We will cover ab initio methods, as well as comparative methods which differ on whether information from other genomes is used as prior information.

Hidden Markov models (HMMs) are the technique of choice for the problem of finding genes in DNA sequences. We will cover the structure of HMMs, the Viterbi algorithm for annotation, the Baum-Welch algorithm for learning models, and pair HMMs to model genefinding in a comparative context. GENSCAN , the paradigmatic example of an ab initio gene finder, will be presented. If time permits, SLAM , a comparative gene finder based on pair HMMs will be introduced.

Since gene finding is complex, our exercise for this portion of the course will be to detect CpG islands on chromosome 22 . We will compare the performance of a global decoding methods (Viterbi decoding) against that of a local method (posterior decoding or smoothing).

Biomarker discovery and supervised learning

The next problem we will cover is that of molecular fingerprinting of disease. This is also known as the biomarker discovery problem. Given mRNA expression levels, or protein levels from normal and diseased cells, the computational problem is of determining biologically significant genes or proteins that are differentially expressed. This is usually the first step in generating causal models of disease. This part of the course draws on the pioneering work of Golub et. al. We will model the problem in the supervised learning framework and introduce k-nearest neighbours and support vector machine classifiers.

In this section of the course, we will analyse the prostate cancer microarray data set from the Broad institute to build classifiers which discriminate between cancer and normal cells. We will also experiment with various feature selection techniques to identify biologically significant genes that are differentially expressed in diseased cells. We will compare the relative effectiveness of global hyperplane classifiers like support vector machines against local methods as exemplified by k-nearest neighbor classifiers.

Systems biology and learning bayesian networks from data

The availability of high-throughput data which reveals the levels of mRNA and proteins in cells and their change over time, makes it possible to construct system level models of cellular activity. The inspiration for this part of the course comes from the 2005 study by Sachs et. al. which uses multi-parameter flow cytometry to reconstruct the T-cell signaling network in humans. The mathematical foundations of Bayesian networks will be covered, as well as the sparse candidate algorithm for learning Bayesian networks from high-throughput data. The use of interventional data to determine causal edges in the network will also be discussed.

The experiment for this section of the course is to use Bayesian network algorithms and the flow cytometry data available from the Science website to recreate the Sachs et. al. derivation of the T-cell signaling network.

Summary of course objectives

This course will teach you

  • how to use the underlying biology to constrain feature and model selection.
  • how to choose and adapt machine learning algorithms for biological problems.
  • how to design learning protocols to deal with incomplete, noisy data.
  • how to interpret the results of machine learning algorithms.

Questions & Answers

where we get a research paper on Nano chemistry....?
Maira Reply
what are the products of Nano chemistry?
Maira Reply
There are lots of products of nano chemistry... Like nano coatings.....carbon fiber.. And lots of others..
Even nanotechnology is pretty much all about chemistry... Its the chemistry on quantum or atomic level
no nanotechnology is also a part of physics and maths it requires angle formulas and some pressure regarding concepts
Preparation and Applications of Nanomaterial for Drug Delivery
Hafiz Reply
Application of nanotechnology in medicine
what is variations in raman spectra for nanomaterials
Jyoti Reply
I only see partial conversation and what's the question here!
Crow Reply
what about nanotechnology for water purification
RAW Reply
please someone correct me if I'm wrong but I think one can use nanoparticles, specially silver nanoparticles for water treatment.
yes that's correct
I think
Nasa has use it in the 60's, copper as water purification in the moon travel.
nanocopper obvius
what is the stm
Brian Reply
is there industrial application of fullrenes. What is the method to prepare fullrene on large scale.?
industrial application...? mmm I think on the medical side as drug carrier, but you should go deeper on your research, I may be wrong
How we are making nano material?
what is a peer
What is meant by 'nano scale'?
What is STMs full form?
scanning tunneling microscope
how nano science is used for hydrophobicity
Do u think that Graphene and Fullrene fiber can be used to make Air Plane body structure the lightest and strongest. Rafiq
what is differents between GO and RGO?
what is simplest way to understand the applications of nano robots used to detect the cancer affected cell of human body.? How this robot is carried to required site of body cell.? what will be the carrier material and how can be detected that correct delivery of drug is done Rafiq
analytical skills graphene is prepared to kill any type viruses .
Any one who tell me about Preparation and application of Nanomaterial for drug Delivery
what is Nano technology ?
Bob Reply
write examples of Nano molecule?
The nanotechnology is as new science, to scale nanometric
nanotechnology is the study, desing, synthesis, manipulation and application of materials and functional systems through control of matter at nanoscale
Is there any normative that regulates the use of silver nanoparticles?
Damian Reply
what king of growth are you checking .?
What fields keep nano created devices from performing or assimulating ? Magnetic fields ? Are do they assimilate ?
Stoney Reply
why we need to study biomolecules, molecular biology in nanotechnology?
Adin Reply
yes I'm doing my masters in nanotechnology, we are being studying all these domains as well..
what school?
biomolecules are e building blocks of every organics and inorganic materials.
how did you get the value of 2000N.What calculations are needed to arrive at it
Smarajit Reply
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Source:  OpenStax, Statistical machine learning for computational biology. OpenStax CNX. Oct 14, 2007 Download for free at http://cnx.org/content/col10455/1.2
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