Filters








488 Hits in 4.6 sec

Structural and Functional Analysis of Multi-Interface Domains

Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li, Jens Kleinjung
2012 PLoS ONE  
We found that about 40% of proteins have the multi-interface property, however the involved multi-interface domains account for only a tiny fraction (1.8%) of the total number of domains.  ...  multi-interface proteins from PDB.  ...  (iii) Aggregate multi-interface proteins into clusters at different SCOP classification levels, i.e., class, fold, superfamily, family, and domain, according to their annotations.  ... 
doi:10.1371/journal.pone.0050821 pmid:23272073 pmcid:PMC3522720 fatcat:egooznsze5b7hcmytzxyq423y4

DISTANCE-BASED IDENTIFICATION OF STRUCTURE MOTIFS IN PROTEINS USING CONSTRAINED FREQUENT SUBGRAPH MINING

Jun Huan, Deepak Bandyopadhyay, Jan Prins, Jack Snoeyink, Alexander Tropsha, Wei Wang
2006 Computational Systems Bioinformatics - Proceedings of the Conference CSB 2006  
The fact that many motifs are highly family-specific can be used to classify new proteins or to provide functional annotation in Structural Genomics Projects.  ...  Using this algorithm, structure motifs were located for several SCOP families including the Eukaryotic Serine Proteases, Nuclear Binding Domains, Papain-like Cysteine Proteases, and FAD/NAD-linked Reductases  ...  and the evolutionary relationship among proteins.  ... 
doi:10.1142/1860947573_0032 fatcat:o4cnzqu3djaufd77mt3u63n7d4

DISTANCE-BASED IDENTIFICATION OF STRUCTURE MOTIFS IN PROTEINS USING CONSTRAINED FREQUENT SUBGRAPH MINING

Jun Huan, Deepak Bandyopadhyay, Jan Prins, Jack Snoeyink, Alexander Tropsha, Wei Wang
2006 Computational Systems Bioinformatics  
The fact that many motifs are highly family-specific can be used to classify new proteins or to provide functional annotation in Structural Genomics Projects.  ...  Using this algorithm, structure motifs were located for several SCOP families including the Eukaryotic Serine Proteases, Nuclear Binding Domains, Papain-like Cysteine Proteases, and FAD/NAD-linked Reductases  ...  and the evolutionary relationship among proteins.  ... 
doi:10.1142/9781860947575_0029 fatcat:kgak76aitngvxgbreluflgsp6a

DISTANCE-BASED IDENTIFICATION OF STRUCTURE MOTIFS IN PROTEINS USING CONSTRAINED FREQUENT SUBGRAPH MINING

Jun Huan, Deepak Bandyopadhyay, Jan Prins, Jack Snoeyink, Alexander Tropsha, Wei Wang
2006 Computational Systems Bioinformatics - Proceedings of the Conference CSB 2006  
The fact that many motifs are highly family-specific can be used to classify new proteins or to provide functional annotation in Structural Genomics Projects.  ...  Using this algorithm, structure motifs were located for several SCOP families including the Eukaryotic Serine Proteases, Nuclear Binding Domains, Papain-like Cysteine Proteases, and FAD/NAD-linked Reductases  ...  and the evolutionary relationship among proteins.  ... 
doi:10.1142/18609475730032 fatcat:tn52h5iflbdg7obuoefh4n7zza

Local Structure Comparison of Proteins [chapter]

Jun Huan, Jan Prins, Wei Wang
2006 Advances in Computers  
We present a new algorithm for this problem that uses a graph-based representation of protein structure and finds recurring subgraphs among a group of protein graphs.  ...  Protein local structure comparison aims to recognize structural similarities between parts of proteins.  ...  In SCOP, the unit of the classification is the domain (e.g. multi-domain proteins are broken into individual domains that are grouped separately).  ... 
doi:10.1016/s0065-2458(06)68005-4 fatcat:5dsp5xan5jccplavjamkklld4i

Detecting Conserved Interaction Patterns in Biological Networks

Mehmet Koyutürk, Yohan Kim, Shankar Subramaniam, Wojciech Szpankowski, Ananth Grama
2006 Journal of Computational Biology  
Graph theoretic formalisms, commonly used for these analysis tasks, often lead to computationally hard problems due to their relation to subgraph isomorphism.  ...  Results: We show, experimentally, that our algorithm can extract frequently occurring patterns in metabolic pathways and protein interaction networks from the KEGG, DIP, and BIND databases within seconds  ...  Specifically, if domain families [40, 41] are used to relate proteins, multi-label nodes are necessary for handling multi-domain proteins.  ... 
doi:10.1089/cmb.2006.13.1299 pmid:17037960 fatcat:qq3ei4c5qjbark2lyws7xwhvdy

From Structure to Function: Methods and Applications

Haim Wolfson, Maxim Shatsky, Dina Schneidman-Duhovny, Oranit Dror, Alexandra Shulman-Peleg, Buyong Ma, Ruth Nussinov
2005 Current protein and peptide science  
Comprehension of protein function at its most basic level requires understanding of molecular interactions.  ...  The rapid increase in experimental data along with recent progress in computational methods has brought modern biology a step closer toward solving one of the most challenging problems: prediction of protein  ...  Protein surface/interface analysis is used to reveal the structure-property relationship of interacting molecules.  ... 
doi:10.2174/1389203053545435 pmid:15853653 fatcat:t6se7n6msnhsfe54rss2xrvnhe

Utilising Graph Machine Learning within Drug Discovery and Development [article]

Thomas Gaudelet, Ben Day, Arian R. Jamasb, Jyothish Soman, Cristian Regep, Gertrude Liu, Jeremy B. R. Hayter, Richard Vickers, Charles Roberts, Jian Tang, David Roblin, Tom L. Blundell (+2 others)
2021 arXiv   pre-print
them, and integrate multi-omic datasets - amongst other data types.  ...  Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between  ...  One of the key characteristics of biomedical data that is produced and used in the drug discovery process is its inter-connected nature.  ... 
arXiv:2012.05716v2 fatcat:kre2kx3x4ff43mmuh7khrxmmzy

Graph Kernels based on High Order Graphlet Parsing and Hashing [article]

Anjan Dutta, Hichem Sahbi
2018 arXiv   pre-print
In order to build our graph representation, we measure the distribution of these graphlets into a given graph, using particular hash functions that efficiently assign sampled graphlets into isomorphic  ...  Graph-based methods are known to be successful in many machine learning and pattern classification tasks.  ...  , that capture isomorphic relationships between graphlets quite accurately.  ... 
arXiv:1803.00425v1 fatcat:b7i5aubyivcanmt7bdxcrclumu

A Survey on Graph Kernels [article]

Nils M. Kriege, Fredrik D. Johansson, Christopher Morris
2019 arXiv   pre-print
Graph kernels have become an established and widely-used technique for solving classification tasks on graphs.  ...  We describe and categorize graph kernels based on properties inherent to their design, such as the nature of their extracted graph features, their method of computation and their applicability to problems  ...  We also evaluated the average inter-agreement between kernels as measured using Fleiss' kappa [133] .  ... 
arXiv:1903.11835v1 fatcat:3rgyn7kbp5h57j5552f2lcdkai

Pattern associativity and the retrieval of semantic networks

Robert Levinson
1992 Computers and Mathematics with Applications  
Method IV is a novel method known as "hierarchical node descriptor method" that is based on the "refinement" method of auhgraph-isomorphism.  ...  The paper concludes by showing how generalization graphs constructed through pattern associativity may also have semantic validity in the domains from which they have been derived.  ...  the method does not actually require the use of conceptual graphs) have also applied it to the retrieval of DNA protein sequences in genetics and to radio signal classification [34] .  ... 
doi:10.1016/0898-1221(92)90125-2 fatcat:rr4qwqxiufffhhtqs6jm3sroaa

Scientific Basis of System Programming

E. M. Lavrischeva
2018 Journal of Software Engineering and Applications  
System APROP was used to create software systems in air defense systems and VMF. The Assembly programming of systems from ready-made reuse and modules is created.  ...  In the method of the Assembly is implemented the theory and practice of transforming non-equivalent types of data transmitted via the interface using the libraries of the 64 functions presented in the  ...  For example, proteins can synthesize from few proteins of DNK in complex structures with specific new properties.  ... 
doi:10.4236/jsea.2018.118025 fatcat:2mrwxk5worhtpbd375gwv3z3ma

Graph-based data mining for biological applications

Leander Schietgat
2011 AI Communications  
In the first part, we study the task of hierarchical multi-label classification (HMC), a variant of classification where an example may belong to multiple classes and where the classes are organised in  ...  The application we focus on is the learning of structure-activity relationships (SAR). Here, the goal is to predict properties of molecules based on their atom-bond structure.  ...  Related work In Sect. 3.2, related work on hierarchical multi-label classification was discussed within the general machine learning domain.  ... 
doi:10.3233/aic-2010-0482 fatcat:kguu6ugombfx7bvfia64d6mqii

Graph Kernels: A Survey

Giannis Nikolentzos, Giannis Siglidis, Michalis Vazirgiannis
2021 The Journal of Artificial Intelligence Research  
Graph kernels have proven successful in a wide range of domains, ranging from social networks to bioinformatics.  ...  During the past 20 years, the considerable research activity that occurred in the field resulted in the development of dozens of graph kernels, each focusing on specific structural properties of graphs  ...  The first family of models operates on the spectral domain and draws on the properties of convolutions in the Fourier domain, while the second family of models operates on the spatial domain where the  ... 
doi:10.1613/jair.1.13225 fatcat:o7whugpf3rd7hf7g7e7gcxhoyi

A survey on graph kernels

Nils M. Kriege, Fredrik D. Johansson, Christopher Morris
2020 Applied Network Science  
Graph kernels have become an established and widely-used technique for solving classification tasks on graphs.  ...  We describe and categorize graph kernels based on properties inherent to their design, such as the nature of their extracted graph features, their method of computation and their applicability to problems  ...  We also evaluated the average inter-agreement between kernels as measured using Fleiss' kappa (Fleiss 1971) .  ... 
doi:10.1007/s41109-019-0195-3 fatcat:xblybuqyf5ezbey7ae6udfexse
« Previous Showing results 1 — 15 out of 488 results