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ACCURATE CLASSIFICATION OF PROTEIN STRUCTURAL FAMILIES USING COHERENT SUBGRAPH ANALYSIS
2003
Biocomputing 2004
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To determine the significance of coherent protein subgraphs, we have conducted an experimental study in which all coherent subgraphs were identified in several protein structural families annotated in ...
The Support Vector Machine algorithm was used to classify proteins from different families under the binary classification scheme. ...
Section 3 presents the results of an experimental study to classify protein structural families using the coherent subgraph mining approach and a case study of identifying fingerprints in the family of ...
doi:10.1142/9789812704856_0039
fatcat:2rt36lnqr5ck7inkvpbb4dcpqm
Frequent subgraph mining for biologically meaningful structural motifs
[article]
2020
bioRxiv
pre-print
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We use frequent subgraph mining to determine all subgraphs that are subgraph isomorphic to, i.e. are contained in, at least a given number of such networks generated from structures in the same protein ...
Finally we use the approach to discover a novel structural motif in jelly-roll capsid proteins found in members of the picornavirus-like superfamily. ...
Coherent subgraph mining [31] for example introduces the use of the mutual information between a subgraph and its subgraphs to identify meaningful subgraphs. ...
doi:10.1101/2020.05.14.095695
fatcat:3bfahgozlvcivg4xwacjox2jg4
Scoring Protein Relationships in Functional Interaction Networks Predicted from Sequence Data
2011
PLoS ONE
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We use the network for predicting functions of uncharacterised proteins. ...
Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure ...
Many thanks to the authors of the freely available libraries for making this work possible.
Author Contributions ...
doi:10.1371/journal.pone.0018607
pmid:21526183
pmcid:PMC3079720
fatcat:vr3oyjqutjcwfdjxirga3kwu2a
Graph-based methods for analysing networks in cell biology
2006
Briefings in Bioinformatics
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Finally, we highlight some challenges in the field and offer our personal view of the key future trends and developments in graph-based analysis of large-scale datasets. ...
The methods are outlined on three levels of increasing complexity, ranging from methods that can characterize global or local structural properties of networks to methods that can detect groups of interconnected ...
In the context of cellular networks, classification aims at constructing a discriminant rule (classifier) that can accurately predict the functional class of an unknown node based on the annotation of ...
doi:10.1093/bib/bbl022
pmid:16880171
fatcat:2f2ogfnaondmligxsp3jdracbe
A Structure-Centric View of Protein Evolution, Design and Adaptation
[article]
2006
arXiv
pre-print
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of structural evolution involves the divergence of protein sequences and structures from one another. ...
Much of this work has focused on the question of how completely new protein structures (i.e. new folds or topologies) are discovered by protein sequences as they evolve. ...
Databases of structural classification are familiar to most protein scientists. ...
arXiv:q-bio/0603028v1
fatcat:3o4cwhwf2jhghicwysyxywso2q
Comprehensive analysis of co-occurring domain sets in yeast proteins
2007
BMC Genomics
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An analysis of this network reveals 99 CDSs that occur in proteins more than expected by chance. ...
Here we study the principles governing domain content of proteins, using yeast as a model species. ...
imply endorsement by the US Government. ...
doi:10.1186/1471-2164-8-161
pmid:17562021
pmcid:PMC1919370
fatcat:jvzoneawaze6zlwolyfdjvzexy
Algorithmic and analytical methods in network biology
2009
Wiley Interdisciplinary Reviews: Systems Biology and Medicine
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The past decade witnessed significant efforts on the development of computational infrastructure for large-scale modeling and analysis of biological systems, commonly using network models. ...
In post-genomic biology, the nature and scale of data that pertain to the structure, function, and organization of biomolecules present novel opportunities for exploratory research. ...
The author would also like to thank Rod Nibbe (CWRU), Mark Chance (CWRU), Shankar Subramaniam (UCSD), and Ananth Grama (Purdue) for many useful discussions. ...
doi:10.1002/wsbm.61
pmid:20836029
pmcid:PMC3087298
fatcat:hfrwmgltzbht5hmwwea4uabjki
A Survey of Computational Methods for Protein Function Prediction
[chapter]
2016
Big Data Analytics in Genomics
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neighbors in a protein-protein interaction network, from microarray data, or a combination of these different types of data. ...
Current methods predict function from a protein's sequence, often in the context of evolutionary relationships, from a protein's three-dimensional structure or specific patterns in the structure, from ...
Work in [222] introduces the concept of k-partite "protein" cliques as functionally coherent but not necessarily dense subgraphs. ...
doi:10.1007/978-3-319-41279-5_7
fatcat:pejwmwpoarhyjhulevmkbavocm
Data Analysis and Bioinformatics
[chapter]
2007
Lecture Notes in Computer Science
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Data analysis methods and techniques are revisited in the case of biological data sets. Particular emphasis is given to clustering and mining issues. ...
Data mining adds to clustering the complications of very large data-sets with many attributes of different types. And this is a typical situation in biology. Some cases studies are also described. ...
folding of a protein; inference of the subcellular location of protein activity; classification of chemical compounds based on structure; special purpose metrics and index structures for phylogenetic applications ...
doi:10.1007/978-3-540-77046-6_47
fatcat:piggpbyzmvclvd5bjduv4nov4m
DSL: Discriminative Subgraph Learning via Sparse Self-Representation
[article]
2019
arXiv
pre-print
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NSP arises in various applications: gene expression samples embedded in a protein-protein interaction (PPI) network, temporal snapshots of infrastructure or sensor networks, and fMRI coherence network ...
subgraphs of features. ...
You, authors of DIPS [8] , for kindly sharing evaluation datasets and the implementation of their algorithm, as well as for several informative discussions. ...
arXiv:1904.00791v1
fatcat:p4xxwv62pbe4pevfwkq56kygey
Graph Theory and Networks in Biology
[article]
2006
arXiv
pre-print
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In this paper, we present a survey of the use of graph theoretical techniques in Biology. ...
hierarchical structure of such networks and network motifs. ...
Science Foundation Ireland is not responsible for any use of data appearing in this publication. ...
arXiv:q-bio/0604006v1
fatcat:nrafbzn7kzdfvkawrfuwqattz4
Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction
2010
BMC Genomics
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Conclusions: The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always ...
This has led to the development of a wide range of methods for predicting protein functions in silico. ...
Acknowledgements We would like to thank Hugues Roest Crollius for critical reading of the manuscript. This work is funded by an Elsa-Neumann scholarship and the Deutsche Forschungsgemeinschaft (DFG). ...
doi:10.1186/1471-2164-11-717
pmid:21171995
pmcid:PMC3017542
fatcat:qqpj3mnbdvdp5djmnc2a5a2mtu
Recent advances in clustering methods for protein interaction networks
2010
BMC Genomics
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The increasing availability of large-scale protein-protein interaction data has made it possible to understand the basic components and organization of cell machinery from the network level. ...
The predictions of protein functions and interactions based on modules will be covered. ...
Acknowledgements This work is supported in part by the National Natural Science Foundation of China under Grant No. 61003124 ...
doi:10.1186/1471-2164-11-s3-s10
pmid:21143777
pmcid:PMC2999340
fatcat:lanqlo4t3bclzhpfryztcbd5qq
Graph theory and networks in Biology
2007
IET Systems Biology
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In this paper, we present a survey of the use of graph theoretical techniques in Biology. ...
hierarchical structure of such networks and network motifs. ...
Science Foundation Ireland is not responsible for any use of data appearing in this publication. ...
doi:10.1049/iet-syb:20060038
pmid:17441552
fatcat:sni2uqu5orbdtdvsab4faqn5c4
Clustering of proximal sequence space for the identification of protein families
2002
Bioinformatics
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Motivation: The study of sequence space, and the deciphering of the structure of protein families and subfamilies, has up to now been required for work in comparative genomics and for the prediction of ...
With the emergence of structural proteomics projects, it is becoming increasingly important to be able to select protein targets for structural studies that will appropriately cover the space of protein ...
The continuous support and interesting discussions of the Protein Design Group members are also acknowledged. ...
doi:10.1093/bioinformatics/18.7.908
pmid:12117788
fatcat:wn5umb55ongb3nk4cy36ndjclu
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