The Resource Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy
Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy
Resource Information
The item Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
- Summary
- "Complex biological systems and their inter-relationships are represented as graphs or networks. The use of graphs to model biological aspects in computational biology, in bioinformatics and biomedicine is currently growing. Graphs enable researchers to easily model relations among objects. Currently in bioinformatics and systems biology there is a growing interest in the analysis of associations among biological molecules at a network level. A main topic of research in this area is represented by the inference and analysis of biological networks from experimental data. Often researchers aim to analyze differences of evolutions among different networks, i.e., networks representing different states of the same reality or networks coming from different species. Consequently, a wide variety of algorithms have been developed to analyze and compare networks. In particular, the comparison of networks is often performed through network alignment algorithms that rely on graph and subgraph isomorphisms. Biological Network Analysis considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The authors discuss various graph-theoretic and data analytics approaches used to analyze these networks with respect to tools, technologies, standards, algorithms, and databases available for generating, representing, and analyzing graphical data." -- Back cover
- Language
- eng
- Label
- Biological network analysis : trends, approaches, graphical theory and algorithms
- Title
- Biological network analysis
- Title remainder
- trends, approaches, graphical theory and algorithms
- Statement of responsibility
- Pietro Hiram Guzzi, Swarup Roy
- Language
- eng
- Summary
- "Complex biological systems and their inter-relationships are represented as graphs or networks. The use of graphs to model biological aspects in computational biology, in bioinformatics and biomedicine is currently growing. Graphs enable researchers to easily model relations among objects. Currently in bioinformatics and systems biology there is a growing interest in the analysis of associations among biological molecules at a network level. A main topic of research in this area is represented by the inference and analysis of biological networks from experimental data. Often researchers aim to analyze differences of evolutions among different networks, i.e., networks representing different states of the same reality or networks coming from different species. Consequently, a wide variety of algorithms have been developed to analyze and compare networks. In particular, the comparison of networks is often performed through network alignment algorithms that rely on graph and subgraph isomorphisms. Biological Network Analysis considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The authors discuss various graph-theoretic and data analytics approaches used to analyze these networks with respect to tools, technologies, standards, algorithms, and databases available for generating, representing, and analyzing graphical data." -- Back cover
- Cataloging source
- YDX
- http://library.link/vocab/creatorDate
- 1980-
- http://library.link/vocab/creatorName
- Guzzi, Pietro Hiram
- Dewey number
- 570.1/51
- Illustrations
- illustrations
- Index
- index present
- LC call number
- QH323.5
- Literary form
- non fiction
- Nature of contents
- dictionaries
- http://library.link/vocab/relatedWorkOrContributorName
- Roy, Swarup
- http://library.link/vocab/subjectName
-
- Biomathematics
- Graph theory
- Label
- Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy
- Bibliography note
- Includes bibliographic references and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Dimensions
- unknown
- Extent
- 1 online resource (189 pages)
- Form of item
- online
- Isbn
- 9780128193518
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations
- Specific material designation
- remote
- System control number
-
- on1154329026
- (OCoLC)1154329026
- Label
- Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy
- Bibliography note
- Includes bibliographic references and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Dimensions
- unknown
- Extent
- 1 online resource (189 pages)
- Form of item
- online
- Isbn
- 9780128193518
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations
- Specific material designation
- remote
- System control number
-
- on1154329026
- (OCoLC)1154329026
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Biological-network-analysis--trends-approaches/fwHilXuc7u8/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Biological-network-analysis--trends-approaches/fwHilXuc7u8/">Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>
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Data Citation of the Item Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/portal/Biological-network-analysis--trends-approaches/fwHilXuc7u8/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/portal/Biological-network-analysis--trends-approaches/fwHilXuc7u8/">Biological network analysis : trends, approaches, graphical theory and algorithms, Pietro Hiram Guzzi, Swarup Roy</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>
