Learn More
We have developed an approach using Bayesian networks to predict protein-protein interactions genome-wide in yeast. Our method naturally weights and combines into reliable predictions genomic features only weakly associated with interaction (e.g., messenger RNAcoexpression, coessentiality, and colocalization). In addition to de novo predictions, it can(More)
To facilitate studies of the yeast proteome, we cloned 5800 open reading frames and overexpressed and purified their corresponding proteins. The proteins were printed onto slides at high spatial density to form a yeast proteome microarray and screened for their ability to interact with proteins and phospholipids. We identified many new calmodulin- and(More)
We investigate the relationship of protein-protein interactions with mRNA expression levels, by integrating a variety of data sources for yeast. We focus on known protein complexes that have clearly defined interactions between their subunits. We find that subunits of the same protein complex show significant coexpression, both in terms of similarities of(More)
Previous research on social values indicates that individuals' own choices as well as their expectations of others' choices in outcome-interdependent situations varies as a function of the weight they typically assign to their own and others' outcomes. The present study extends this research in that it investigates differences in individuals'(More)
Currently, there is a major effort to map protein-protein interactions on a genome-wide scale. The utility of the resulting interaction networks will depend on the reliability of the experimental methods and the coverage of the approaches. Known macromolecular complexes provide a defined and objective set of protein interactions with which to compare(More)
The concept of 'protein function' is rather 'fuzzy' because it is often based on whimsical terms or contradictory nomenclature. This currently presents a challenge for functional genomics because precise definitions are essential for most computational approaches. Addressing this challenge, the notion of networks between biological entities (including(More)
BACKGROUND Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to(More)
Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based(More)
We analyzed 10 genome expression data sets by large-scale cross-referencing against broad structural and functional categories. The data sets, generated by different techniques (e.g. SAGE and gene chips), provide various representations of the yeast transcriptome (the set of all yeast genes, weighted by transcript abundance). Our analysis enabled us to(More)
The TGF-beta pathway plays a central role in tissue homeostasis and morphogenesis. It transduces a variety of extracellular signals into intracellular transcriptional responses that control a plethora of cellular processes, including cell growth, apoptosis, and differentiation. We use computational modeling to show that coupling of signaling with receptor(More)