共查询到20条相似文献,搜索用时 15 毫秒
1.
Modifying the DPClus algorithm for identifying protein complexes based on new topological structures 总被引:4,自引:0,他引:4
Background
Identification of protein complexes is crucial for understanding principles of cellular organization and functions. As the size of protein-protein interaction set increases, a general trend is to represent the interactions as a network and to develop effective algorithms to detect significant complexes in such networks. 相似文献2.
Background
How to detect protein complexes is an important and challenging task in post genomic era. As the increasing amount of protein-protein interaction (PPI) data are available, we are able to identify protein complexes from PPI networks. However, most of current studies detect protein complexes based solely on the observation that dense regions in PPI networks may correspond to protein complexes, but fail to consider the inherent organization within protein complexes. 相似文献3.
Background
Many functional proteins have a symmetric structure. Most of these are multimeric complexes, which are made of non-symmetric monomers arranged in a symmetric manner. However, there are also a large number of proteins that have a symmetric structure in the monomeric state. These internally symmetric proteins are interesting objects from the point of view of their folding, function, and evolution. Most algorithms that detect the internally symmetric proteins depend on finding repeating units of similar structure and do not use the symmetry information. 相似文献4.
Chao Wu Fan Zhang Xia Li Shihua Zhang Jiang Li Fei Su Kongning Li Yuqing Yan 《BMC systems biology》2010,4(1):82
Background
Functional modules are basic units of cell function, and exploring them is important for understanding the organization, regulation and execution of cell processes. Functional modules in single biological networks (e.g., the protein-protein interaction network), have been the focus of recent studies. Functional modules in the integrated network are composite functional modules, which imply the complex relationships involving multiple biological interaction types, and detect them will help us understand the complexity of cell processes. 相似文献5.
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Background
Solenoid repeat proteins of the Tetratrico Peptide Repeat (TPR) family are involved as scaffolds in a broad range of protein-protein interactions. Several resources are available for the prediction of TPRs, however, they often fail to detect divergent repeat units. 相似文献8.
Background
Whereas T cell receptors (TCRs) detect peptide/major histocompatibility complexes (pMHCs) with exquisite specificity, there are challenges regarding their expression and use as soluble detection molecules due to molecular instability. We have investigated strategies for the production of TCR-immunoglobulin (Ig) fusion proteins. Two different TCRs that are characteristic of a mouse model for idiotype (Id) dependent immune regulation were engineered. They are structurally unrelated with different variable (V), diversity (D) and joining (J) segments, but each share one V gene segment, either Vα or Vβ, with the well characterized murine TCR, 2C. 相似文献9.
Background
The idea that the assembly of protein complexes is linked with protein disorder has been inferred from a few large complexes, such as the viral capsid or bacterial flagellar system, only. The relationship, which suggests that larger complexes have more disorder, has never been systematically tested. The recent high-throughput analyses of protein-protein interactions and protein complexes in the cell generated data that enable to address this issue by bioinformatic means. 相似文献10.
Background
During apoptosis, Ca2+-dependent events participate in the regulation of intracellular and morphological changes including phosphatidylserine exposure in the exoplasmic leaflet of the cell plasma membrane. The occurrence of phosphatidylserine at the surface of specialized cells, such as platelets, is also essential for the assembly of the enzyme complexes of the blood coagulation cascade, as demonstrated by hemorrhages in Scott syndrome, an extremely rare genetic deficiency of phosphatidylserine externalization, without other apparent pathophysiologic consequences. We have recently reported a reduced capacitative Ca2+ entry in Scott cells which may be part of the Scott phenotype. 相似文献11.
12.
Development and implementation of an algorithm for detection of protein complexes in large interaction networks 总被引:4,自引:0,他引:4
Md Altaf-Ul-Amin Yoko Shinbo Kenji Mihara Ken Kurokawa Shigehiko Kanaya 《BMC bioinformatics》2006,7(1):207-13
Background
After complete sequencing of a number of genomes the focus has now turned to proteomics. Advanced proteomics technologies such as two-hybrid assay, mass spectrometry etc. are producing huge data sets of protein-protein interactions which can be portrayed as networks, and one of the burning issues is to find protein complexes in such networks. The enormous size of protein-protein interaction (PPI) networks warrants development of efficient computational methods for extraction of significant complexes. 相似文献13.
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Background
Nucleosomes are the basic structural units of eukaryotic chromatin and play a key role in regulation of gene expression. After resolution of the nucleosome structure, the bipartite nature of this particle has revealed itself and has disclosed the presence, on the histone surface, of a symmetric distribution of positive charges, able to interact with their negative DNA phosphate counterpart. 相似文献15.
Background
The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. 相似文献16.
Background
Exposure of cells to environmental stress conditions can lead to the interruption of several intracellular processes, in particular those performed by macromolecular complexes such as the spliceosome. 相似文献17.
Randall McNally Gregory D Bowman Eric R Goedken Mike O'Donnell John Kuriyan 《BMC structural biology》2010,10(1):3
Background
Sliding clamps, such as Proliferating Cell Nuclear Antigen (PCNA) in eukaryotes, are ring-shaped protein complexes that encircle DNA and enable highly processive DNA replication by serving as docking sites for DNA polymerases. In an ATP-dependent reaction, clamp loader complexes, such as the Replication Factor-C (RFC) complex in eukaryotes, open the clamp and load it around primer-template DNA. 相似文献18.
Background
Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes. The systematic analysis of PPI networks can enable a great understanding of cellular organization, processes and function. In this paper, we investigate the problem of protein complex detection from noisy protein interaction data, i.e., finding the subsets of proteins that are closely coupled via protein interactions. However, protein complexes are likely to overlap and the interaction data are very noisy. It is a great challenge to effectively analyze the massive data for biologically meaningful protein complex detection.Results
Many people try to solve the problem by using the traditional unsupervised graph clustering methods. Here, we stand from a different point of view, redefining the properties and features for protein complexes and designing a “semi-supervised” method to analyze the problem. In this paper, we utilize the neural network with the “semi-supervised” mechanism to detect the protein complexes. By retraining the neural network model recursively, we could find the optimized parameters for the model, in such a way we can successfully detect the protein complexes. The comparison results show that our algorithm could identify protein complexes that are missed by other methods. We also have shown that our method achieve better precision and recall rates for the identified protein complexes than other existing methods. In addition, the framework we proposed is easy to be extended in the future.Conclusions
Using a weighted network to represent the protein interaction network is more appropriate than using a traditional unweighted network. In addition, integrating biological features and topological features to represent protein complexes is more meaningful than using dense subgraphs. Last, the “semi-supervised” learning model is a promising model to detect protein complexes with more biological and topological features available.19.
Oxana Sorokina Anita Kapus Kata Terecskei Laura E Dixon Laszlo Kozma-Bognar Ferenc Nagy Andrew J Millar 《Journal of biological engineering》2009,3(1):15-16
Background
Advances in synthetic biology will require spatio-temporal regulation of biological processes in heterologous host cells. We develop a light-switchable, two-hybrid interaction in yeast, based upon the Arabidopsis proteins PHYTOCHROME A and FAR-RED ELONGATED HYPOCOTYL 1-LIKE. Light input to this regulatory module allows dynamic control of a light-emitting LUCIFERASE reporter gene, which we detect by real-time imaging of yeast colonies on solid media. 相似文献20.
Nikolay A. Barinov Irina I. Vlasova Alexey V. Sokolov Valeria A. Kostevich Evgeniy V. Dubrovin Dmitry V. Klinov 《Biochimica et Biophysica Acta (BBA)/General Subjects》2018,1862(12):2862-2868