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#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
IDENTIFICATION OF BOOLEAN NETWORKS USING PREMINED NETWORK
TOPOLOGY INFORMATION
ABSTRACT
Boolean network (BN) has been a powerful tool for system biology and Boolean
dynamical system. The successful applications of BN include gene regulatory networks, artificial
neural network, social network, multiagent systems, and so on. These applications are based on
the identification of the BNs. But it is difficult to identify the BNs directly due to the lack of
tools for the logical system.
EXISTING SYSTEM
To solve this problem, several approaches were proposed within the framework of
identifying logical relations directly. For example, a general reverse engineering algorithm used
information theoretic principles to reduce the search space. Using the STP, Cheng proved that
the data required could be reduced considerably when some special structure properties of BNs
are known. To the best of our knowledge, the specific methodology to obtain the structural
information from the observed data has not been investigated yet and still remains challenging.
DIS ADVANTAGES
 To identify BNs large amount of data is required.
PROPOSED SYSTEM
In this brief, a novel approach is proposed to reduce the data requirement in the
identification of BNs. Instead of removing fabricated dependence from a fully connected
network, our approach mines the topology by adding each true dependence into an empty
topology. First, a matching table is created to reflect the dependence relationships among nodes
and to provide an approach to reduce the comparisons in the identification. Then, a dynamic
locating matching pair (DLMP) approach for extracting location parameters from dynamic time
series is given, which can be regarded as a dynamic extension to the matching table. Next, based
on the pseudo commutative property of the STP, a position-transform mining (PTM) algorithm is
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
put forward to improve the data utilization. With the determination of the dependence
relationships among nodes, the network topology information is obtained. The premined
topology information can be used to identify the BNs.
ADVANTAGES
 Reduce the data requirement in the identification of BNs.
MODULES
 Matching Table
 Dynamic Locating Matching Pairs
 Position-Transforms Mining
SYSTEM REQUIREMENTS
H/W System Configuration:-
Processor - Pentium –III
RAM - 256 MB (min)
Hard Disk - 20 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
S/W System Configuration:-
Operating System : Windows95/98/2000/XP
Application Server : Tomcat5.0/6.X
Front End : HTML, Jsp
Scripts : JavaScript.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
Server side Script : Java Server Pages.
Database : MySQL 5.0
Database Connectivity : JDBC

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Identification of boolean networks using premined

  • 1. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com IDENTIFICATION OF BOOLEAN NETWORKS USING PREMINED NETWORK TOPOLOGY INFORMATION ABSTRACT Boolean network (BN) has been a powerful tool for system biology and Boolean dynamical system. The successful applications of BN include gene regulatory networks, artificial neural network, social network, multiagent systems, and so on. These applications are based on the identification of the BNs. But it is difficult to identify the BNs directly due to the lack of tools for the logical system. EXISTING SYSTEM To solve this problem, several approaches were proposed within the framework of identifying logical relations directly. For example, a general reverse engineering algorithm used information theoretic principles to reduce the search space. Using the STP, Cheng proved that the data required could be reduced considerably when some special structure properties of BNs are known. To the best of our knowledge, the specific methodology to obtain the structural information from the observed data has not been investigated yet and still remains challenging. DIS ADVANTAGES  To identify BNs large amount of data is required. PROPOSED SYSTEM In this brief, a novel approach is proposed to reduce the data requirement in the identification of BNs. Instead of removing fabricated dependence from a fully connected network, our approach mines the topology by adding each true dependence into an empty topology. First, a matching table is created to reflect the dependence relationships among nodes and to provide an approach to reduce the comparisons in the identification. Then, a dynamic locating matching pair (DLMP) approach for extracting location parameters from dynamic time series is given, which can be regarded as a dynamic extension to the matching table. Next, based on the pseudo commutative property of the STP, a position-transform mining (PTM) algorithm is
  • 2. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com put forward to improve the data utilization. With the determination of the dependence relationships among nodes, the network topology information is obtained. The premined topology information can be used to identify the BNs. ADVANTAGES  Reduce the data requirement in the identification of BNs. MODULES  Matching Table  Dynamic Locating Matching Pairs  Position-Transforms Mining SYSTEM REQUIREMENTS H/W System Configuration:- Processor - Pentium –III RAM - 256 MB (min) Hard Disk - 20 GB Key Board - Standard Windows Keyboard Mouse - Two or Three Button Mouse Monitor - SVGA S/W System Configuration:- Operating System : Windows95/98/2000/XP Application Server : Tomcat5.0/6.X Front End : HTML, Jsp Scripts : JavaScript.
  • 3. #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 / 6066663 Mo: +91 9500218218 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com Server side Script : Java Server Pages. Database : MySQL 5.0 Database Connectivity : JDBC