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This course is a short series of lectures on Statistical Bioinformatics. Topics covered are listed in the Table of Contents. The notes were preparedby Ewa Paszek, Lukasz Wita and Marek Kimmel. The development of this course has been supported by NSF 0203396 grant.

Gene networks.

A gene regulatory network (also called a GRN or genetic regulatory network, ) is a collection of DNA segments in a cell which interact with each other and with other substances in the cell, thereby governing the rates at which genes are transcribed into mRNA. Genes can be viewed as nodes in such a network, with input being proteins such as transcription factors , and outputs being the level of gene expression. The node itself can also be viewed as a function which can be obtained by combining basic functions upon the inputs (in the Boolean network these are boolean functions or gates computed using the basic AND OR and NOT gates in electronics). These functions have been interpreted as performing a kind information processing within cell which determine cellular behaviour. The basic drivers within cells are levels of some proteins, which determine both spatial (tissue related) and temporal (developmental stage) co-ordinates of the cell, as a kind of "cellular memory". The gene networks are only beginning to be understood, and it is a next step for biology to attempt to deduce the functions for each gene "node", to assist in modeling behaviour of a cell. Mathematical models of GRNs have been developed to allow predictions of the models to be tested. Various modeling techniques have been used, including boolean networks, Petri nets, Bayesian networks, and sets of differential equations. Conversely, techniques have been proposed for generating models of GRNs that best explain a set of time series observations.

One gene can affect the expression of another gene by binding of the gene product of one gene to the promoter region of another gene. Looking at more than two genes, we refer to the regulatory network as the regulatory interactions between the genes. If we have a large number of measurements of the expression level of a number of genes, we should be able to model or reverse engineer the regulatory network that controls their expression level. The problem can be attacked in two fundamentally different ways: using time-series data and using steady-state data of gene knockout.

GRNs act as analog biochemical computers to specify the identity and level of expression of groups of target genes. Central to this computation are DNA recognition sequences with which transcription factors associate. When active transcription factors associate with the promontory region of target genes, they can function to specifically repress (down-regulate) or induce (up-regulate) synthesis of the corresponding RNA. The immediate molecular output of a gene regulatory network is the constellation of RNAs and proteins encoded by network target genes. The resulting cellular outputs are changes in the structure, metabolic capacity, or behavior of the cell mediated by new expression of up-regulated proteins and elimination of down-regulated proteins.

GRNs are remarkably diverse in their structure, but several basic properties are illustrated in the figure below (Figure1.) . In this example, two different signals converge on a single target gene where the cis-regulatory elements provide for an integrated output in response to the two inputs. Signal molecule A triggers the conversion of inactive transcription factor A (green oval) into an active form that binds directly to the target gene's cis-regulatory sequence. The process for signal B is more complex. Signal B triggers the separation of inactive B (red oval) from an inhibitory factor (yellow rectangle). B is then free to form an active complex that binds to the active A transcription factor on the cis-regulatory sequence. The net output is expression of the target gene at a level determined by the action of factors A and B. In this way, cis-regulatory DNA sequences, together with the proteins that assemble on them, integrate information from multiple signaling inputs to produce an appropriately regulated readout. A more realistic network might contain multiple target genes regulated by signal A alone, others by signal B alone, and still others by the pair of A and B. Co-regulated target genes often code for proteins that act together to build a specific cell structure or to effect a concerted change in cell function. For example, genes encoding components of the multiprotein proteasome machine (see The Machines of Life) are co-regulated at the RNA level. This was shown by microarray gene chip analyses in yeast cells, and each gene was found to possess a similar cis-regulatory DNA sequence that mediates binding of a particular transcription factor. Similarly, a bacterium may respond to a shortage of its preferred energy source by activating expression of genes whose protein products function in a biochemical pathway that allows it to use a different, more abundant source of energy.

The gene regulatory network.

Boolean Networks
Probabilistic Boolean Networks
Bayesian Networks

Questions & Answers

what is microbiology
Agebe Reply
What is a cell
Odelana Reply
what is cell
Mohammed
how does Neisseria cause meningitis
Nyibol Reply
what is microbiologist
Muhammad Reply
what is errata
Muhammad
is the branch of biology that deals with the study of microorganisms.
Ntefuni Reply
What is microbiology
Mercy Reply
studies of microbes
Louisiaste
when we takee the specimen which lumbar,spin,
Ziyad Reply
How bacteria create energy to survive?
Muhamad Reply
Bacteria doesn't produce energy they are dependent upon their substrate in case of lack of nutrients they are able to make spores which helps them to sustain in harsh environments
_Adnan
But not all bacteria make spores, l mean Eukaryotic cells have Mitochondria which acts as powerhouse for them, since bacteria don't have it, what is the substitution for it?
Muhamad
they make spores
Louisiaste
what is sporadic nd endemic, epidemic
Aminu Reply
the significance of food webs for disease transmission
Abreham
food webs brings about an infection as an individual depends on number of diseased foods or carriers dully.
Mark
explain assimilatory nitrate reduction
Esinniobiwa Reply
Assimilatory nitrate reduction is a process that occurs in some microorganisms, such as bacteria and archaea, in which nitrate (NO3-) is reduced to nitrite (NO2-), and then further reduced to ammonia (NH3).
Elkana
This process is called assimilatory nitrate reduction because the nitrogen that is produced is incorporated in the cells of microorganisms where it can be used in the synthesis of amino acids and other nitrogen products
Elkana
Examples of thermophilic organisms
Shu Reply
Give Examples of thermophilic organisms
Shu
advantages of normal Flora to the host
Micheal Reply
Prevent foreign microbes to the host
Abubakar
they provide healthier benefits to their hosts
ayesha
They are friends to host only when Host immune system is strong and become enemies when the host immune system is weakened . very bad relationship!
Mark
what is cell
faisal Reply
cell is the smallest unit of life
Fauziya
cell is the smallest unit of life
Akanni
ok
Innocent
cell is the structural and functional unit of life
Hasan
is the fundamental units of Life
Musa
what are emergency diseases
Micheal Reply
There are nothing like emergency disease but there are some common medical emergency which can occur simultaneously like Bleeding,heart attack,Breathing difficulties,severe pain heart stock.Hope you will get my point .Have a nice day ❣️
_Adnan
define infection ,prevention and control
Innocent
I think infection prevention and control is the avoidance of all things we do that gives out break of infections and promotion of health practices that promote life
Lubega
Heyy Lubega hussein where are u from?
_Adnan
en français
Adama
which site have a normal flora
ESTHER Reply
Many sites of the body have it Skin Nasal cavity Oral cavity Gastro intestinal tract
Safaa
skin
Asiina
skin,Oral,Nasal,GIt
Sadik
How can Commensal can Bacteria change into pathogen?
Sadik
How can Commensal Bacteria change into pathogen?
Sadik
all
Tesfaye
by fussion
Asiina
what are the advantages of normal Flora to the host
Micheal
what are the ways of control and prevention of nosocomial infection in the hospital
Micheal
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Source:  OpenStax, Introduction to bioinformatics. OpenStax CNX. Oct 09, 2007 Download for free at http://cnx.org/content/col10240/1.3
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