| |
BMC Bioinformatics, Vol. 11, No. 1. (07 January 2010), 14.
Abstract
BACKGROUND:Large datasets of protein interactions provide a rich resource for the discovery of Short Linear Motifs (SLiMs) that recur in unrelated proteins. However, existing methods for estimating the probability of motif recurrence may be biased by the size and composition of the search dataset, such that p-value estimates from different datasets, or from motifs containing different numbers of non-wildcard positions, are not strictly comparable. Here, we develop more exact methods and explore the potential biases of computationally efficient approximations.RESULTS:A widely used ...
|
| |
BMC bioinformatics, Vol. 10, No. 1. (2009), 402.
Abstract
BACKGROUND: Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. RESULTS: This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes ...
|
| |
PLoS Biol In PLoS Biol, Vol. 7, No. 11. (24 November 2009), e1000247.
Abstract
Scientists and clinicians who study genetic alterations and disease have traditionally described phenotypes in natural language. The considerable variation in these free-text descriptions has posed a hindrance to the important task of identifying candidate genes and models for human diseases and indicates the need for a computationally tractable method to mine data resources for mutant phenotypes. In this study, we tested the hypothesis that ontological annotation of disease phenotypes will facilitate the discovery of new genotype-phenotype relationships within and across species. ...
|
| |
Bioinformatics In Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3183-3184.
Abstract
Summary: The increasing number of available atomic 3D structures of transmembrane channel proteins represents a valuable resource for better understanding their structure-function relationships and to eventually predict their selectivity. Herein, we present PoreLogo, an automatic tool for analysing, visualizing and comparing the amino acid composition of transmembrane channels and its conservation across the corresponding protein family. Availability: PoreLogo is accessible as a public web server at http://www.ebi.ac.uk/thornton-srv/software/PoreLogo/. Contacts: marial@ebi.ac.uk; romina.oliva@uniparthenope.it. 10.1093/bioinformatics/btp545 ...
|
| |
Bioinformatics In Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3166-3173.
Abstract
Motivation: Functional module detection within protein interaction networks is a challenging problem due to the sparsity of data and presence of errors. Computational techniques for this task range from purely graph theoretical approaches involving single networks to alignment of multiple networks from several species. Current network alignment methods all rely on protein sequence similarity to map proteins across species. Results: Here we carry out network alignment using a protein functional similarity measure. We show that using functional similarity to map ...
|
| |
Bioinformatics (Oxford, England) In Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3143-3150.
Abstract
MOTIVATION: Clustering of protein-protein interaction networks is one of the most common approaches for predicting functional modules, protein complexes and protein functions. But, how well does clustering perform at these tasks? RESULTS: We develop a general framework to assess how well computationally derived clusters in physical interactomes overlap functional modules derived via the Gene Ontology (GO). Using this framework, we evaluate six diverse network clustering algorithms using Saccharomyces cerevisiae and show that (i) the performances of these algorithms can differ substantially ...
|
| |
Bioinformatics In Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3121-3127.
Abstract
Motivation: Type 2 diabetes is a chronic metabolic disease that involves both environmental and genetic factors. To understand the genetics of type 2 diabetes and insulin resistance, the DIabetes Genome Anatomy Project (DGAP) was launched to profile gene expression in a variety of related animal models and human subjects. We asked whether these heterogeneous models can be integrated to provide consistent and robust biological insights into the biology of insulin resistance. Results: We perform integrative analysis of the 16 DGAP ...
|
| |
Bioinformatics In Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3108-3113.
Abstract
Motivation: Structural features at protein-protein interfaces can be studied to understand protein-protein interactions. It was noticed that in a dataset of 45 multimeric proteins the interface could either be described as flat against flat or protruding/interwound. In the latter, residues within one chain were surrounded by those in other chains, whereas in the former they were not. Results: A simple method was developed that could distinguish between these two types with results that matched those made by a human annotator. ...
|
| |
Bioinformatics In Bioinformatics, Vol. 25, No. 23. (1 December 2009), pp. 3049-3055.
Abstract
MicroRNAs (miRNAs) are a class of short endogenously expressed RNA molecules that regulate gene expression by binding directly to the messenger RNA of protein coding genes. They have been found to confer a novel layer of genetic regulation in a wide range of biological processes. Computational miRNA target prediction remains one of the key means used to decipher the role of miRNAs in development and disease. Here we introduce the basic idea behind the experimental identification of miRNA targets and present ...
|
| |
Bioinformatics In Bioinformatics, Vol. 25, No. 24. (15 December 2009), pp. 3207-3212.
Abstract
Motivation: Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here, we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE). Results: We generated 16 million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these ...
|
| |
Journal of Molecular Biology, Vol. 324, No. 1. (15 November 2002), pp. 177-192.
Abstract
Protein–protein interactions play crucial roles in biological processes. Experimental methods have been developed to survey the proteome for interacting partners and some computational approaches have been developed to extend the impact of these experimental methods. Computational methods are routinely applied to newly discovered genes to infer protein function and plausible protein–protein interactions. Here, we develop and extend a quantitative method that identifies interacting proteins based upon the correlated behavior of the evolutionary histories of protein ligands and their receptors. We have ...
|
| |
Bioinformatics, Vol. 25, No. 22. (15 November 2009), pp. 2913-2920.
Abstract
Motivation: In general, each cell signaling pathway involves many proteins, each with one or more specific roles. As they are essential components of cell activity, it is important to understand how these proteins work--and in particular, to determine which of the species' proteins participate in each role. Experimentally determining this mapping of proteins to roles is difficult and time consuming. Fortunately, many pathways are similar across species, so we may be able to use known pathway information of one species to ...
|
| |
Bioinformatics (Oxford, England), Vol. 25, No. 22. (15 November 2009), pp. 2962-2968.
Abstract
MOTIVATION: The existing supervised methods for biological network inference work on each of the networks individually based only on intra-species information such as gene expression data. We believe that it will be more effective to use genomic data and cross-species evolutionary information from different species simultaneously, rather than to use the genomic data alone. RESULTS: We created a new semi-supervised learning method called Link Propagation for inferring biological networks of multiple species based on genome-wide data and evolutionary information. The new ...
|
| |
Bioinformatics (Oxford, England), Vol. 25, No. 22. (15 November 2009), pp. 3043-3044.
Abstract
FuncAssociate is a web application that discovers properties enriched in lists of genes or proteins that emerge from large-scale experimentation. Here we describe an updated application with a new interface and several new features. For example, enrichment analysis can now be performed within multiple gene- and protein-naming systems. This feature avoids potentially serious translation artifacts to which other enrichment analysis strategies are subject. AVAILABILITY: The FuncAssociate web application is freely available to all users at http://llama.med.harvard.edu/funcassociate. ...
|
| |
Bioinformatics (Oxford, England), Vol. 25, No. 21. (1 November 2009), pp. 2780-2786.
Abstract
MOTIVATION: The power of a microarray experiment derives from the identification of genes differentially regulated across biological conditions. To date, differential regulation is most often taken to mean differential expression, and a number of useful methods for identifying differentially expressed (DE) genes or gene sets are available. However, such methods are not able to identify many relevant classes of differentially regulated genes. One important example concerns differentially co-expressed (DC) genes. RESULTS: We propose an approach, gene set co-expression analysis (GSCA), to ...
|
| |
Bioinformatics, Vol. 25, No. 21. (1 November 2009), pp. 2787-2794.
Abstract
Motivation: Deregulated signaling cascades are known to play a crucial role in many pathogenic processes, among them are tumor initiation and progression. In the recent past, modern experimental techniques that allow for measuring the amount of mRNA transcripts of almost all known human genes in a tissue or even in a single cell have opened new avenues for studying the activity of the signaling cascades and for understanding the information flow in the networks. Results: We present a novel dynamic ...
|
| |
Bioinformatics (Oxford, England), Vol. 25, No. 21. (1 November 2009), pp. 2855-2856.
Abstract
MOTIVATION: With the availability of many 'omics' data, such as transcriptomics, proteomics or metabolomics, the integrative or joint analysis of multiple datasets from different technology platforms is becoming crucial to unravel the relationships between different biological functional levels. However, the development of such an analysis is a major computational and technical challenge as most approaches suffer from high data dimensionality. New methodologies need to be developed and validated. RESULTS: integrOmics efficiently performs integrative analyses of two types of 'omics' variables that ...
|
| |
PLoS computational biology, Vol. 5, No. 9. (25 September 2009), e1000513.
Abstract
microRNAs (miRNAs) are major regulators of gene expression and thereby modulate many biological processes. Computational methods have been instrumental in understanding how miRNAs bind to mRNAs to induce their repression but have proven inaccurate. Here we describe a novel method that combines expression data from human and mouse to discover conserved patterns of expression between orthologous miRNAs and mRNA genes. This method allowed us to predict thousands of putative miRNA targets. Using the luciferase reporter assay, we confirmed 4 out of ...
|
| |
Bioinformatics, Vol. 22, No. 15. (1 August 2006), pp. 1921-1923.
Abstract
Summary: NETGEN is an event-driven simulator that creates phylogenetic networks by extending the birth-death model to include diploid hybridizations. DNA sequences are evolved in conjunction with the topology, enabling hybridization decisions to be based on contemporary evolutionary distances. NETGEN supports variable rate lineages, root sequence specification, outgroup generation and many other options. This note describes the NETGEN application and proposes an extension of the Newick format to accommodate phylogenetic networks. Availability: NETGEN is written in C and is available in ...
|
| |
Bioinformatics, Vol. 24, No. 22. (15 November 2008), pp. 2608-2614.
Abstract
Motivation: Microarray expression data reveal functionally associated proteins. However, most proteins that are associated are not actually in direct physical contact. Predicting physical interactions directly from microarrays is both a challenging and important task that we addressed by developing a novel machine learning method optimized for this task. Results: We validated our support vector machine-based method on several independent datasets. At the same levels of accuracy, our method recovered more experimentally observed physical interactions than a conventional correlation-based approach. Pairs ...
|
| |
Genome Biology, Vol. 5, No. 4. (2004), 215.
Abstract
Improvements in the fields of membrane-protein molecular biology and biochemistry, technical advances in structural data collection and processing, and the availability of numerous sequenced genomes have paved the way for membrane-protein structural genomics efforts. There has been significant recent progress, but various issues essential for high-throughput membrane-protein structure determination remain to be resolved. ...
|
| |
Nucl. Acids Res., Vol. 33, No. suppl_2. (1 July 2005), pp. W331-336.
Abstract
Prism (http://gordion.hpc.eng.ku.edu.tr/prism) is a website for protein interface analysis and prediction of putative protein-protein interactions. It is composed of a database holding protein interface structures derived from the Protein Data Bank (PDB). The server also includes summary information about related proteins and an interactive protein interface viewer. A list of putative protein-protein interactions obtained by running our prediction algorithm can also be accessed. These results are applied to a set of protein structures obtained from the PDB at the time of ...
|
| |
Nucl. Acids Res., Vol. 32, No. suppl_2. (1 July 2004), pp. W576-581.
Abstract
Meta-BASIC (http://basic.bioinfo.pl) is a novel sensitive approach for recognition of distant similarity between proteins based on consensus alignments of meta profiles. Specifically, Meta-BASIC compares sequence profiles combined with predicted secondary structure by utilizing several scoring systems and alignment algorithms. In our benchmarking tests, Meta-BASIC outperforms many individual servers, including fold recognition servers, and it can compete with meta predictors that base their strength on the structural comparison of models. In addition, Meta-BASIC, which enables detection of very distant relationships even if ...
|
| |
Genome Research, Vol. 9, No. 11. (1 November 1999), pp. 1106-1115.
Abstract
10.1101/gr.9.11.1106 Analysis procedures are needed to extract useful information from the large amount of gene expression data that is becoming available. This work describes a set of analytical tools and their application to yeast cell cycle data. The components of our approach are (1) a similarity measure that reduces the number of false positives, (2) a new clustering algorithm designed specifically for grouping gene expression patterns, and (3) an interactive graphical cluster analysis tool that allows user feedback and validation. We ...
|
| |
Current Opinion in Structural Biology In Nucleic acids / Sequences and topology, Vol. 18, No. 3. (June 2008), pp. 342-348.
Abstract
Depending on whether similar structures are found in the PDB library, the protein structure prediction can be categorized into template-based modeling and free modeling. Although threading is an efficient tool to detect the structural analogs, the advancements in methodology development have come to a steady state. Encouraging progress is observed in structure refinement which aims at drawing template structures closer to the native; this has been mainly driven by the use of multiple structure templates and the development of hybrid knowledge-based ...
|
| |
Journal of molecular biology, Vol. 287, No. 4. (9 April 1999), pp. 797-815.
Abstract
A new protein fold recognition method is described which is both fast and reliable. The method uses a traditional sequence alignment algorithm to generate alignments which are then evaluated by a method derived from threading techniques. As a final step, each threaded model is evaluated by a neural network in order to produce a single measure of confidence in the proposed prediction. The speed of the method, along with its sensitivity and very low false-positive rate makes it ideal for automatically ...
|
| |
|
| |
Annual review of biophysics and biomolecular structure, Vol. 29 (2000), pp. 291-325.
Abstract
Comparative modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. The number of protein sequences that can be modeled and the accuracy of the predictions are increasing steadily because of the growth in the number of known protein structures and because of the improvements in the modeling software. Further advances are ...
|
| |
In Bioinformatics Algorithms: Techniques and Applications (2008), pp. 465-490.
|
| |
Bioinformatics, Vol. 20, No. 18. (12 December 2004), pp. 3346-3352.
Abstract
Motivation: High-throughput protein interaction detection methods are strongly affected by false positive and false negative results. Focused experiments are needed to complement the large-scale methods by validating previously detected interactions but it is often difficult to decide which proteins to probe as interaction partners. Developing reliable computational methods assisting this decision process is a pressing need in bioinformatics. Results: We show that we can use the conserved properties of the protein network to identify and validate interaction candidates. We apply ...
|
| |
Nucleic acids research, Vol. 35, No. Database issue. (12 January 2007), pp. D561-565.
by S. Kerrien, Y. Alam-Faruque, B. Aranda, et al.I. Bancarz, A. Bridge, C. Derow, E. Dimmer, M. Feuermann, A. Friedrichsen, R. Huntley, C. Kohler, J. Khadake, C. Leroy, A. Liban, C. Lieftink, L. Montecchi-Palazzi, S. Orchard, J. Risse, K. Robbe, B. Roechert, D. Thorneycroft, Y. Zhang, R. Apweiler, H. Hermjakob
Abstract
IntAct is an open source database and software suite for modeling, storing and analyzing molecular interaction data. The data available in the database originates entirely from published literature and is manually annotated by expert biologists to a high level of detail, including experimental methods, conditions and interacting domains. The database features over 126,000 binary interactions extracted from over 2100 scientific publications and makes extensive use of controlled vocabularies. The web site provides tools allowing users to search, visualize and download data ...
|
| |
Nucl. Acids Res., Vol. 32, No. suppl_1. (1 January 2004), pp. D449-451.
Abstract
The Database of Interacting Proteins (http://dip.doe-mbi.ucla.edu) aims to integrate the diverse body of experimental evidence on protein-protein interactions into a single, easily accessible online database. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies ...
|
| |
Nucleic acids research, Vol. 35, No. Database issue. (12 January 2007), pp. D572-574.
Abstract
The Molecular INTeraction database (MINT, http://mint.bio.uniroma2.it/mint/) aims at storing, in a structured format, information about molecular interactions (MIs) by extracting experimental details from work published in peer-reviewed journals. At present the MINT team focuses the curation work on physical interactions between proteins. Genetic or computationally inferred interactions are not included in the database. Over the past four years MINT has undergone extensive revision. The new version of MINT is based on a completely remodeled database structure, which offers more efficient data ...
|
| |
Nature Biotechnology, Vol. 23, No. 12. (01 December 2005), pp. 1499-1501.
Abstract
Clustering is often one of the first steps in gene expression analysis. How do clustering algorithms work, which ones should we use and what can we expect from them? ...
|
| |
Journal of molecular evolution, Vol. 44, No. 1. (January 1997), pp. 66-73.
Abstract
An approach for genome comparison, combining function classification of gene products and sequence comparison, is presented. The genomes of Haemophilus influenzae and Escherichia coli are analyzed, and all genes are classified into nine major functional classes, corresponding to important cellular processes. To study gene order relationships and genome organization in the two bacteria, we performed statistics on neighboring pairs of genes. To estimate the significance of the observations, a statistical model based on binomial distributions has been developed. Significant patterns of ...
|
| |
Nucl. Acids Res., Vol. 30, No. 7. (1 April 2002), pp. 1575-1584.
Abstract
Detection of protein families in large databases is one of the principal research objectives in structural and functional genomics. Protein family classification can significantly contribute to the delineation of functional diversity of homologous proteins, the prediction of function based on domain architecture or the presence of sequence motifs as well as comparative genomics, providing valuable evolutionary insights. We present a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families. The method relies on the Markov cluster ...
|
| |
Nature, Vol. 402, No. 6757. (04 November 1999), pp. 86-90.
Abstract
A large-scale effort to measure, detect and analyse protein–protein interactions using experimental methods is under way1, 2. These include biochemistry such as co-immunoprecipitation or crosslinking, molecular biology such as the two-hybrid system or phage display, and genetics such as unlinked noncomplementing mutant detection3. Using the two-hybrid system4, an international effort to analyse the complete yeast genome is in progress5. Evidently, all these approaches are tedious, labour intensive and inaccurate6. From a computational perspective, the question is how can we predict that ...
|
| |
Nature, Vol. 402, No. 6757. (4 November 1999), pp. 83-86.
Abstract
The availability of over 20 fully sequenced genomes has driven the development of new methods to find protein function and interactions. Here we group proteins by correlated evolution, correlated messenger RNA expression patterns and patterns of domain fusion to determine functional relationships among the 6,217 proteins of the yeast Saccharomyces cerevisiae. Using these methods, we discover over 93,000 pairwise links between functionally related yeast proteins. Links between characterized and uncharacterized proteins allow a general function to be assigned to more than ...
|
| |
Science, Vol. 306, No. 5705. (24 December 2004), pp. 2246-2249.
Abstract
A major focus of genome research is to decipher the networks of molecular interactions that underlie cellular function. We describe a computational approach for identifying detailed relationships between proteins on the basis of genomic data. Logic analysis of phylogenetic profiles identifies triplets of proteins whose presence or absence obey certain logic relationships. For example, protein C may be present in a genome only if proteins A and B are both present. The method reveals many previously unidentified higher order relationships. These ...
|
| |
IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 1, No. 1. (2004), pp. 13-23.
Abstract
Phylogenetic networks model the evolutionary history of sets of organisms when events such as hybrid speciation and horizontal gene transfer occur. In spite of their widely acknowledged importance in evolutionary biology, phylogenetic networks have so far been studied mostly for specific data sets. We present a general definition of phylogenetic networks in terms of directed acyclic graphs (DAGs) and a set of conditions. Further, we distinguish between model networks and reconstructible ones and characterize the effect of extinction and taxon sampling ...
|
| |
PLoS Comput Biol, Vol. 1, No. 1. (24 June 2005), e3.
Abstract
An important element of the developing field of proteomics is to understand protein-protein interactions and other functional links amongst genes. Across-species correlation methods for detecting functional links work on the premise that functionally linked proteins will tend to show a common pattern of presence and absence across a range of genomes. We describe a maximum likelihood statistical model for predicting functional gene linkages. The method detects independent instances of the correlated gain or loss of pairs of proteins on phylogenetic trees, ...
|
| |
Proceedings of the National Academy of Sciences of the United States of America, Vol. 96, No. 8. (13 April 1999), pp. 4285-4288.
Abstract
Determining protein functions from genomic sequences is a central goal of bioinformatics. We present a method based on the assumption that proteins that function together in a pathway or structural complex are likely to evolve in a correlated fashion. During evolution, all such functionally linked proteins tend to be either preserved or eliminated in a new species. We describe this property of correlated evolution by characterizing each protein by its phylogenetic profile, a string that encodes the presence or absence of ...
|
| |
Bioinformatics, Vol. 21, No. 17. (30 June 2005), pp. bti564-3489.
Abstract
Motivation: The prediction of protein-protein interactions is currently an important issue of bioinformatics. The mirror tree method uses evolutionary information to predict protein-protein interactions. However, it has been recognized that predictions by the mirror tree method lead to many false positives. The incentive of our study was to solve this problem by improving the method of extracting the co-evolutionary information about the protein pairs.Results: We developed a novel method to predict protein-protein interactions from co-evolutionary information in the framework of the ...
|
| |
Genome Research, Vol. 19, No. 10. (20 October 2009), pp. 1861-1871.
Abstract
10.1101/gr.092452.109 Coevolution maintains interactions between phenotypic traits through the process of reciprocal natural selection. Detecting molecular coevolution can expose functional interactions between molecules in the cell, generating insights into biological processes, pathways, and the networks of interactions important for cellular function. Prediction of interaction partners from different protein families exploits the property that interacting proteins can follow similar patterns and relative rates of evolution. Current methods for detecting coevolution based on the similarity of phylogenetic trees or evolutionary distance matrices have, ...
|
| |
Journal of molecular biology, Vol. 352, No. 4. (30 September 2005), pp. 1002-1015.
Abstract
The identification of the whole set of protein interactions taking place in an organism is one of the main tasks in genomics, proteomics and systems biology. One of the computational techniques used by many investigators for studying and predicting protein interactions is the comparison of evolutionary histories (phylogenetic trees), under the hypothesis that interacting proteins would be subject to a similar evolutionary pressure resulting in a similar topology of the corresponding trees. Here, we present a new approach to predict protein ...
|
| |
Proteins, Vol. 47, No. 2. (1 May 2002), pp. 219-227.
Abstract
Deciphering the interaction links between proteins has become one of the main tasks of experimental and bioinformatic methodologies. Reconstruction of complex networks of interactions in simple cellular systems by integrating predicted interaction networks with available experimental data is becoming one of the most demanding needs in the postgenomic era. On the basis of the study of correlated mutations in multiple sequence alignments, we propose a new method (in silico two-hybrid, i2h) that directly addresses the detection of physically interacting protein pairs ...
|
| |
Journal of Molecular Biology, Vol. 299, No. 2. (02 June 2000), pp. 283-293.
Abstract
The divergent evolution of proteins in cellular signaling pathways requires ligands and their receptors to co-evolve, creating new pathways when a new receptor is activated by a new ligand. However, information about the evolution of binding specificity in ligand-receptor systems is difficult to glean from sequences alone. We have used phosphoglycerate kinase (PGK), an enzyme that forms its active site between its two domains, to develop a standard for measuring the co-evolution of interacting proteins. The N-terminal and C-terminal domains of ...
|
| |
Protein Eng., Vol. 14, No. 9. (1 September 2001), pp. 609-614.
Abstract
Deciphering the network of protein interactions that underlines cellular operations has become one of the main tasks of proteomics and computational biology. Recently, a set of bioinformatics approaches has emerged for the prediction of possible interactions by combining sequence and genomic information. Even though the initial results are very promising, the current methods are still far from perfect. We propose here a new way of discovering possible protein-protein interactions based on the comparison of the evolutionary distances between the sequences of ...
|
| |
Nature Chemical Biology, Vol. 4, No. 11. (20 October 2008), pp. 666-673.
Abstract
Biological interaction networks have been in the scientific limelight for nearly a decade. Increasingly, the concept of network biology and its various applications are becoming more commonplace in the community. Recent years have seen networks move from pretty pictures with limited application to solid concepts that are increasingly used to understand the fundamentals of biology. They are no longer merely results of postgenome analysis projects, but are now the starting point of many of the most exciting new scientific developments. We ...
|
| |
The EMBO Journal, Vol. 22, No. 14. (15 July 2003), pp. 3486-3492.
Abstract
In this review, we discuss the structural and functional diversity of protein–protein interactions (PPIs) based primarily on protein families for which three-dimensional structural data are available. PPIs play diverse roles in biology and differ based on the composition, affinity and whether the association is permanent or transient. In vivo, the protomer's localization, concentration and local environment can affect the interaction between protomers and are vital to control the composition and oligomeric state of protein complexes. Since a change in quaternary state ...
|
Search
Search
