Msi Molecular Sciences Institute

Programs: Significant activitiesresearch at vtt/msi molecular sciences institute (msi) enables the quantitative prediction of the behaviors of biological systems. To this end, msi emphasizes the creation of tools and techniques for generating biological information, the development of computational and analytical frameworks for integrating this data, and the design and engineering of biological systems. The goal of institute scientists is to significantly advance our understanding of how living systems function and evolve. One way that institute scientists disseminate findings from their research activities is through peer-reviewed publications. Below we present select recent publications from the institute:select publicationszdraljevic s, wagner d, cheng k, ruohonen l, jntti j, penttil m, resnekov o, pesce cg. (2013)single cell measurements of enzyme level as a predictive tool for cellular fates during organic acidproduction. Appl environ microbiol. 2013 sep 13. [epub ahead of print] pmid:24038690pincus, d. , ryan, c. , smith, r. D. , brent, r. , and resnekov, o. (2013) assigning quatitative function topost-translational modifications reveals multiple sites of phosphorylation that tune yeast pheromonesignaling output. Published 12 mar 2013 | plos one 10. 1371/journal. Pone. 0056544flanigon j, kamali-moghaddam m, burbulis i, annink c, steffen m, oeth p, brent r, van den boom d,landegren u and cantor c. (2012) multiplex protein detection with dna readout via mass spectrometry. N biotechnol. Nov 28. Doi:pii: s1871-6784(12)00860-6. 10. 1016/j. Nbt. 2012. 11. 003. [epub ahead of print]. Bush a, chernomoretz a, yu r, gordon a. And colman-lerner a. (2012) using cell-id 1. 4 with r formicroscope-based cytometry. Curr protoc mol biol. Oct; chapter 14:unit 14. 18. Doi:10. 1002/0471142727. Mb1418s100. 2). Denby, c. M. , im, j. H. , yu, r. C. , pesce, g. And brem, r. B. (2012) negative feedback confers mutationalrobustness in yeast transcription factor regulation. Proc. Natl. Acad. Sci. Usa. Mar 6: 109(10):3874-3878. Thomson tm, benjamin kr, bush a, love t, pincus d, resnekov o, yu rc, gordon a, colman-lernera, endy d and brent r. (2011) scaffold number in yeast signaling system sets tradeoff between systemoutput and dynamic range. Proc. Natl. Acad. Sci. Usa. Dec 13;108(50):20265-70. Epub 2011 nov 23. Pincus d, benjamin k, burbulis i, tsong ae and resnekov o. (2010) reagents for investigating mapksignalling in model yeast species. Yeast. 2010 jul;27(7):423-30. Andrews ss, addy nj, brent r and arkin ap. (2010) detailed simulations of cell biology with smoldyn2. 1. Plos comput biol. Mar 12;6(3):e1000705. Andrews ss. (2009) accurate particle-based simulation of adsorption, desorption and partial transmission. Phys biol. 2009 nov 12;6(4):046015. Yu, r. C. , pesce, c. G. , colman-lerner, a. , lok, l. ,pincus, d. , serra, e. , holl, m. , benjamin, k. , gordon,a. , and brent , r. (2008) feedback that improves information transmission in yeast signalling. Nature 456:755-761. Yu rc, resnekov o, abola ap, andrews ss, benjamin kr, bruck j, burbulis ie, colman-lerner a, endyd, gordon a, holl m, lok l, pesce cg, serra e, smith rd, thomson tm, tsong ae and brent r. (2008)the alpha project: a model system for systems biology research. Iet syst biol. 2008 sep;2(5):222-33. Review. Burbulis, i. , yamaguchi, k. , yu, r. , resnekov o. , and brent, r. (2007) quantifying small numbers ofmolecules with a "near-universal" protein-dna chimera. Nat methods, 12:1011-3. Gordon a, colman-lerner a, chin te, benjamin kr, yu, r. C. , brent r: (2007) single-cell quantificationof molecules and rates using open-source microscope-based cytometry. Nat methods. Burbulis i, yamaguchi k, gordon a, carlson r, brent r: (2005) using protein-dna chimeras to detectand count small numbers of molecules. Nat methods, 2:31-37. Fy13 auditcolman-lerner a, gordon a, serra e, chin t, resnekov o, endy d, pesce cg, brent r (2005) regulatedcell-to-cell variation in a cell-fate decision system. Nature, 437:699-706. Lok l, brent r: (2005) automatic generation of cellular reaction networks with moleculizer 1. 0. Natbiotechnol, 23:131-136. Lok l: (2004) the need for speed in stochastic simulation. Nat biotechnol, 22:964-965. Lok l: (2002) pathfinder and other tools for analyzing signal transduction networks. Ann n y acad sci,971:589-594. Burbulis ie, winkel-shirley b: (1999) interactions among enzymes of the arabidopsis flavonoidbiosynthetic pathway. Proc natl acad sci u s a, 96:12929-12934. Webb cd, resnekov o: (1999) use of green fluorescent protein for visualization for cell-specific geneexpression and subcellular protein localization in bacillus subtilis. Methods enzymol, 302:136-153.