MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract 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. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Més noticies a l'entorn del període americà de Josep Pijoan Soteras (1881-1963)

[cat] El coneixement de la trajectòria dels catalans exiliats, com és el cas de Josep Pijoan Soteras, Francesc Cambó Batlle i Josep Gudiol Ricart, entre altres, és fascinant perquè permet comprendre i valorar el seu itinerari personal, alhora que projecta un dramàtic resplendor sobre la cultura catalana de l"època. En aquest article es plantegen dues qüestions. La primera se centra en Pijoan com a agent d"art, aspecte molt poc conegut fi ns ara; mentre que en la segona part tracta de Pijoan com a escriptor d'art i la problemàtica que es va produir amb motiu de la seva intervenció en el llibre Les pintures romàniques de Catalunya dins la «Monumenta Cataloniae», col·lecció patrocinada per Francesc Cambó.[eng]Knowledge of the pathways of Catalan exiles -as in the case of Jose Pijoan Soteras, Francesc Cambó Batlle and Jose Gudiol Ricart, among others- is fascinating because it permits understanding and evaluation of their personal itineraires while at the same time casting a dramatic light on Catalan culture of the epoch. In this article two questions are presented: the first is centered on Pijoan as an art dealer, an aspect very little known until now, while the second deals with Pijoan as a writer on art and the problems raised by his participation in the book on Romanesque painters of Catalonia in the «Monumenta Cataloniae», the collection of whitch Francesc Cambó was patron