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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

How we are making nano material?
what is a peer
What is meant by 'nano scale'?
What is STMs full form?
scanning tunneling microscope
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.
anyone know any internet site where one can find nanotechnology papers?
Damian Reply
sciencedirect big data base
Introduction about quantum dots in nanotechnology
Praveena Reply
what does nano mean?
Anassong Reply
nano basically means 10^(-9). nanometer is a unit to measure length.
do you think it's worthwhile in the long term to study the effects and possibilities of nanotechnology on viral treatment?
Damian Reply
absolutely yes
how to know photocatalytic properties of tio2 nanoparticles...what to do now
Akash Reply
it is a goid question and i want to know the answer as well
characteristics of micro business
for teaching engĺish at school how nano technology help us
How can I make nanorobot?
Do somebody tell me a best nano engineering book for beginners?
s. Reply
there is no specific books for beginners but there is book called principle of nanotechnology
how can I make nanorobot?
what is fullerene does it is used to make bukky balls
Devang Reply
are you nano engineer ?
fullerene is a bucky ball aka Carbon 60 molecule. It was name by the architect Fuller. He design the geodesic dome. it resembles a soccer ball.
what is the actual application of fullerenes nowadays?
That is a great question Damian. best way to answer that question is to Google it. there are hundreds of applications for buck minister fullerenes, from medical to aerospace. you can also find plenty of research papers that will give you great detail on the potential applications of fullerenes.
what is the Synthesis, properties,and applications of carbon nano chemistry
Abhijith Reply
Mostly, they use nano carbon for electronics and for materials to be strengthened.
is Bucky paper clear?
carbon nanotubes has various application in fuel cells membrane, current research on cancer drug,and in electronics MEMS and NEMS etc
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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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