Download e-book for iPad: Statistical and Machine Learning Approaches for Network by Matthias Dehmer

By Matthias Dehmer

ISBN-10: 0470195150

ISBN-13: 9780470195154

Statistical and laptop studying techniques for community research offers an available framework for structurally examining graphs through bringing jointly identified and novel methods on graph sessions and graph measures for class. via offering varied ways in line with experimental facts, the booklet uniquely units itself except the present literature through exploring the applying of computer studying suggestions to numerous forms of complicated networks. made from chapters written via the world over well known researchers within the box of interdisciplinary community concept, the ebook offers present and classical ways to learn networks statistically. equipment from laptop studying, information mining, and data concept are strongly emphasised all through.

Show description

Read Online or Download Statistical and Machine Learning Approaches for Network Analysis PDF

Similar graph theory books

Download e-book for kindle: Graph Theory and Applications: With Exercises and Problems by Jean-Claude Fournier

Content material: bankruptcy 1 uncomplicated recommendations (pages 21–43): bankruptcy 2 bushes (pages 45–69): bankruptcy three hues (pages 71–82): bankruptcy four Directed Graphs (pages 83–96): bankruptcy five seek Algorithms (pages 97–118): bankruptcy 6 optimum Paths (pages 119–147): bankruptcy 7 Matchings (pages 149–172): bankruptcy eight Flows (pages 173–195): bankruptcy nine Euler excursions (pages 197–213): bankruptcy 10 Hamilton Cycles (pages 26–236): bankruptcy eleven Planar Representations (pages 237–245): bankruptcy 12 issues of reviews (pages 247–259): bankruptcy A Expression of Algorithms (pages 261–265): bankruptcy B Bases of Complexity conception (pages 267–276):

Download e-book for iPad: Theory and Application of Graphs by Junming Xu (auth.)

Within the spectrum of arithmetic, graph idea which experiences a mathe­ matical constitution on a collection of parts with a binary relation, as a famous self-discipline, is a relative newcomer. In fresh 3 a long time the fascinating and speedily growing to be region of the topic abounds with new mathematical devel­ opments and important functions to real-world difficulties.

Extra info for Statistical and Machine Learning Approaches for Network Analysis

Sample text

15. J. Faith, B. T. Thaden, I. Mogno, J. Wierzbowski, G. Cottarel, S. J. S. Gardner, Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles, PLoS Biol. 5(1), e8 (2007). 16. E. Meyer, K. Kontos, F. Lafitte, G. Bontempi, Information-theoretic inference of large transcriptional regulatory networks, EUROSIP j. Bioinfor. Syst. Biol. 2007 79879, (2007). 17. J. Kubica, A. Moore, D. Cohn, J. Schneider, cGraph: a fast graph based method for link analysis and queries, Proceedings of IJCAI Text-Mining and Link-Analysis Workshop, Acapulco, Mexico, 2003.

52(1), 99–112 (1988). 30. J. Newman, E. Leicht, Mixture models and exploratory analysis in networks. PNAS, 104(23), 9564–9569 (2007). 31. N. Raghavan, R. Albert, S. Kumara, Near linear time algorithm to detect community structures in large-scale networks, Phys. Rev. E 76(3), 036106 (2007). 32. D. O. S. Qin, A. Swaroop, High throughput screening of co-expressed gene pairs with controlled False Discovery Rate (FDR) and Minimum Acceptable Strength (MAS), J. Comput. Biol. 12(7), 1027–1043 (2005). 33.

Driessche, J. O. Booth, P. Hill, P. Juvan, B. Zupan, A. Kuspa, G. Shaulsky, Epistasis analysis with global transcriptional phenotypes, Nat. Genet. 37(5), 471–477 (2005). 68. D. L. Dequ´eant, H. Li, Comparative analysis of distance based clustering methods, in Analysis of Microarray Data: A Network Based Approach, (F. Emmert-Streib, M. ), Wiley-VCH, Weinheim, Germany, 2007. 69. G. Altay, F. Emmert-Streib, Revealing differences in gene network inference algorithms on the network level by ensemble methods, Bioinformatics 26(14), 1738–1744 (2010).

Download PDF sample

Statistical and Machine Learning Approaches for Network Analysis by Matthias Dehmer

by Thomas

Rated 4.56 of 5 – based on 22 votes