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Current
Bioinformatics
ISSN: 1574-8936
Current Bioinformatics
Volume 4, Number 1, January 2009
Contents
A Review of the Primer Approximation Multiplex PCR (PAMP)
Technique for Detecting Large Scale Cancer Genomic Lesions
Pp. 1-7
Kedsuda Apichonbancha, Bhaskar Dasgupta,
Jin Jun, Ion Mandoiu and Emma Mendonca
[Abstract] [Full
text article]
Computational Biology of Olfactory Receptors
Pp. 8-15
Chiquito J. Crasto
[Abstract] [Full
text article]
Molecular Genetic Markers: Discovery,
Applications, Data Storage and Visualisation Pp.
16-27
Chris Duran, Nikki Appleby, David Edwards
and Jacqueline Batley
[Abstract] [Full
text article]
Digital Signal Processing in the Analysis
of Genomic Sequences Pp. 28-40
Juan V. Lorenzo-Ginori, Aníbal Rodríguez-Fuentes,
Ricardo Grau Ábalo and Robersy Sánchez
Rodríguez
[Abstract] [Full
text article]
Software for Determination of Biological
Age Pp. 41-47
Kartlos J. Kachiashvili and David
Yu. Melikdzhanian
[Abstract] [Full
text article]
‘Load Points’ and ‘Choke
Points’ as Nodes for Prioritizing Drug Targets in
Pseudomonas aeruginosa Pp. 48-53
Deepak Perumal, Chu Sing Lim, Kishore R.
Sakharkar and Meena K. Sakharkar
[Abstract] [Full
text article]
Structural Bioinformatics: From the Sequence
to Structure and Function Pp. 54-87
Marco Wiltgen
[Abstract] [Full
text article]
Abstracts
[Back to top]
A Review of the Primer Approximation Multiplex PCR
(PAMP) Technique for Detecting Large Scale Cancer Genomic
Lesions
Kedsuda Apichonbancha, Bhaskar Dasgupta,
Jin Jun, Ion Mandoiu and Emma Mendonca
[Full
text article]
Primer Approximation Multiplex PCR (PAMP) is a recently
introduced experimental technique for detecting large-scale
cancer genome lesions such as inversions and deletions from
heterogeneous samples containing a mixture of cancer and normal
cells. In this chapter we will first review previous solutions
for the problem of selecting sets of PAMP primers that minimize
detection failure probability and subsequently review our
approach based on integer programming formulations for inversion
and deletion detections.
[Back to top]
Computational Biology of Olfactory Receptors
Chiquito J. Crasto
[Full
text article]
Olfactory receptors, in addition to being involved in
first step of the physiological processes that leads to olfaction,
occupy an important place in mammalian genomes. ORs constitute
super families in these genomes. Elucidating olfactory receptor
function at a molecular level can be aided by a computationally
derived structure and an understanding of its interactions
with odor molecules. Experimental functional analyses of olfactory
receptors in conjunction with computational studies serve
to validate findings and generate hypotheses. We present here
a review of the research efforts in: creating computational
models of olfactory receptors, identifying binding strategies
for these receptors with odorant molecules, performing medium
to long range simulation studies of odor ligands in the receptor
binding region, and identifying amino acid positions within
the receptor that are responsible for ligand-binding and olfactory
receptor activation. Written as a primer and a teaching tool,
this review will help researchers extend the methodologies
described herein to other GPCRs.
[Back to top]
Molecular Genetic Markers: Discovery, Applications, Data Storage
and Visualisation
Chris Duran, Nikki Appleby, David Edwards
and Jacqueline Batley
[Full
text article]
Molecular genetic markers represent one of the most powerful
tools for the analysis of genomes and enable the association
of heritable traits with underlying genomic variation. Molecular
marker technology has developed rapidly over the last decade
and two forms of sequence based marker, Simple Sequence Repeats
(SSRs), also known as microsatellites, and Single Nucleotide
Polymorphisms (SNPs) now predominate applications in modern
genetic analysis. The reducing cost of DNA sequencing has
led to the availability of large sequence data sets derived
from whole genome sequencing and large scale Expressed Sequence
Tag (EST) discovery that enable the mining of SSRs and SNPs,
which may then be applied to diversity analysis, genetic trait
mapping, association studies, and marker assisted selection.
These markers are inexpensive, require minimal labour to produce
and can frequently be associated with annotated genes. Here
we review automated methods for the discovery of SSRs and
SNPs and provide an overview of the diverse applications of
these markers.
[Back to top]
Digital Signal Processing in the Analysis of Genomic Sequences
Juan V. Lorenzo-Ginori, Aníbal Rodríguez-Fuentes,
Ricardo Grau Ábalo and Robersy Sánchez
Rodríguez
[Full
text article]
Digital Signal Processing (DSP) applications in Bioinformatics
have received great attention in recent years, where new effective
methods for genomic sequence analysis, such as the detection
of coding regions, have been developed. The use of DSP principles
to analyze genomic sequences requires defining an adequate
representation of the nucleotide bases by numerical values,
converting the nucleotide sequences into time series. Once
this has been done, all the mathematical tools usually employed
in DSP are used in solving tasks such as identification of
protein coding DNA regions, identification of reading frames,
and others. In this article we present an overview of the
most relevant applications of DSP algorithms in the analysis
of genomic sequences, showing the main results obtained by
using these techniques, analyzing their relative advantages
and drawbacks, and providing relevant examples. We finally
analyze some perspectives of DSP in Bioinformatics, considering
recent research results on algebraic structures of the genetic
code, which suggest other new DSP applications in this field,
as well as the new field of Genomic Signal Processing.
[Back to top]
Software for Determination of Biological Age
Kartlos J. Kachiashvili and David
Yu. Melikdzhanian
[Full
text article]
An original software package for determination of biological
age has been offered. The package is simple for understanding
and convenient in application. It is designed for the users
who are not professionals in the fields of applied statistics
or computer science. The problems and the algorithms realized
in the package, the features and the possibilities of their
application are described in brief.
The package can be used both for fundamental theoretical research
in which various logical-mathematical methods of determination
of biological age are compared with each other and for applied
work in a geriatric clinic.
[Back to top]
‘Load Points’ and ‘Choke Points’ as
Nodes for Prioritizing Drug Targets in Pseudomonas aeruginosa
Deepak Perumal, Chu Sing Lim, Kishore R.
Sakharkar and Meena K. Sakharkar
[Full
text article]
Biological pathways information has accumulated along
with Genomic sequence data. These metabolic pathways help
us in understanding network robustness and complex reaction
networks. They also provide a framework for improved understanding
of microbial physiology and for antimicrobial drug discovery.
This article is an attempt to understand the local and global
properties of metabolic networks in P. aeruginosa
and to identify potential drug targets through ‘load
point’ and ‘choke point’ analyses. In this
study, we identify 25 choke point enzymes in pathways unique
to P. aeruginosa and 202 choke point enzymes in the
common pathways between the pathogen and the host human. We
also list top 10 choke point enzymes based on the load point
values and number of shortest paths and propose them as putative
targets. These data underscore the utility of systems analyses
methods for understanding human metabolic network in drug
discovery process and in-depth understanding of the mechanism
of diseases.
[Back to top]
Structural Bioinformatics: From the Sequence to Structure
and Function
Marco Wiltgen
[Full
text article]
Proteins are the molecules of life which are involved
in cellular processes. The functional specificity of a protein
is linked to its structure. A great section of bioinformatics
deals with the prediction, analysis and visualization of protein
3D structures. High-throughput methods for the determination
of protein structures provide the information needed to build
structure-activity relationships. The accessibility of these
structural data together with genomic and clinical data is
of crucial importance for the application of bioinformatics
in medical research. The experimental methods are supplemented
by homology modelling, where new protein structures are predicted
by exploiting structural information from known configurations.
Computer visualization of protein models provide insights
into biological processes which can not be adequately explained
otherwise. For the analysis of protein-protein interactions,
Voronoi tessellations are used to quantify the macromolecular
interfaces. Details at the atomic and electronic levels of
the protein molecules, needed for a deeper understanding of
properties that remain unrevealed after structural elucidation,
are provided by methods based on quantum theoretical calculations.
Many proteins are of immediate medical and pharmacological
relevance. The structural analysis is therefore of special
interest to understand diseases at a molecular level, which
is the prerequisite for new developments in diagnosis and
therapy.
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