419 Hits in 6.7 sec


2003 Biocomputing 2004  
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]

Sebastian Keller, Pauli Miettinen, Olga V. Kalinina
2020 bioRxiv   pre-print
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

Gaston K. Mazandu, Nicola J. Mulder, Christophe Herman
2011 PLoS ONE  
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

T. Aittokallio
2006 Briefings in Bioinformatics  
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]

Eric J. Deeds, Eugene I. Shakhnovich
2006 arXiv   pre-print
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

Inbar Cohen-Gihon, Ruth Nussinov, Roded Sharan
2007 BMC Genomics  
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

Mehmet Koyutürk
2009 Wiley Interdisciplinary Reviews: Systems Biology and Medicine  
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]

Amarda Shehu, Daniel Barbará, Kevin Molloy
2016 Big Data Analytics in Genomics  
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]

Vito Di Gesù
2007 Lecture Notes in Computer Science  
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]

Lin Zhang, Petko Bogdanov
2019 arXiv   pre-print
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]

Oliver Mason, Mark Verwoerd
2006 arXiv   pre-print
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

Samira Jaeger, Christine T Sers, Ulf Leser
2010 BMC Genomics  
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

Jianxin Wang, Min Li, Youping Deng, Yi Pan
2010 BMC Genomics  
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

O. Mason, M. Verwoerd
2007 IET Systems Biology  
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

F. Abascal, A. Valencia
2002 Bioinformatics  
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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