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Introduction

Cells are the building blocks of life, and they come in many forms and shapes, from self-sustained bacteria to highly specialized neurons in the human brain. At a glance, cells might come across as small bags filled with proteins and DNA, but a closer look reveals a high degree of spatial and temporal organization. Proteins associate in large assemblies or complexes which seemingly reorganize in a context dependent manner and the cell division is strictly controlled temporally so that each step in the cycle is carried out in order. Understanding this organization will give us an opportunity to gain insight into diseases at the molecular level. Understanding disease at the molecular level will be fundamentally important when developing tomorrows therapeutics.

Research

The study of the organization of cells sometimes called systems biology, and as the name suggest, one approach biology from a systemic point of view. My research group is approaching this from two different angles, where the first is to model protein abundance regulation by accurately measure protein abundance on a systemic level and the second is to understand how proteins assemble into complexes.

One of the fundamentals is to understand what each proteins roll is in the cell. It is time consuming to study each individual protein and hence, we attempt to address the issue of incomplete protein function annotation by bioinformatical means. In this and this article we address protein structure annotations by pure computational means and in this article, we annotated about 100 uncharacterized proteins in yeast by integrating structure prediction technology with three high-throughput technologies to assign molecular function, biological process and cellular location.

References

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4. Drew, Kevin; Winters, Patrick; Butterfoss, Glenn; Berstis, Viktors; Uplinger, Keith; Armstrong, Jonathan; Riffle, Michael; Schweighofer, Erik; Bovermann, Bill; Goodlett, David; Davis, Trisha; Shasha, Dennis; Malmstrom, Lars; Bonneau, Richard; The proteome folding project: Proteome-scale prediction of structure and function. Genome Res (2011), 21: 1981-94.
3. Malmstrom, Lars; Riffle, Michael; Strauss, Charlie; Chivian, Dylan; Davis, Trisha; Bonneau, Richard; Baker, David; Superfamily Assignments for the Yeast Proteome through Integration of Structure Prediction with the Gene Ontology. PLoS Biol (2007), 5: e76.
2. Hazbun, Tony; Malmstrom, Lars; Anderson, Scott; Graczyk, Beth; Fox, Bethany; Riffle, Michael; Sundin, Bryan; Aranda, J; McDonald, W; Chiu, Chun-Hwei; Snydsman, Brian; Bradley, Phillip; Muller, Eric; Fields, Stanley; Baker, David; Yates, John; Davis, Trisha; Assigning function to yeast proteins by integration of technologies. Mol Cell (2003), 12: 1353-65.
1. Bonneau, Richard; Strauss, Charlie; Rohl, Carol; Chivian, Dylan; Bradley, Phillip; Malmstrom, Lars; Robertson, Tim; Baker, David; De Novo Prediction of Three-dimensional Structures for Major Protein Families. J Mol Biol (2002), 322: 65.