Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

The Molecular and Mathematical Basis of Waddington's Epigenetic Landscape: A Framework for post-Darwinian Biology?

Abstract: The Neo-Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo-Darwinism. It needs to incorporate the non-linear, stochastic dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric 'epigenetic landscape', which actually represents the quasi-potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re-wiring of regulatory interactions - offering a link between genetic mutation and sudden, broad evolutionary changes.

Experimental protein mixture for validating tandem mass spectral analysis.

Abstract: Several methods have been used to identify peptides that correspond to tandem mass spectra. In this work, we describe a data set of low energy tandem mass spectra generated from a control mixture of known protein components that can be used to evaluate the accuracy of these methods. As an example, these spectra were searched by the SEQUEST application against a human peptide sequence database. The numbers of resulting correct and incorrect peptide assignments were then determined. We show how the sensitivity and error rate are affected by the use of various filtering criteria based upon SEQUEST scores and the number of tryptic termini of assigned peptides.

A high-quality catalog of the Drosophila melanogaster proteome.

Abstract: Understanding how proteins and their complex interaction networks convert the genomic information into a dynamic living organism is a fundamental challenge in biological sciences. As an important step towards understanding the systems biology of a complex eukaryote, we cataloged 63% of the predicted Drosophila melanogaster proteome by detecting 9,124 proteins from 498,000 redundant and 72,281 distinct peptide identifications. This unprecedented high proteome coverage for a complex eukaryote was achieved by combining sample diversity, multidimensional biochemical fractionation and analysis-driven experimentation feedback loops, whereby data collection is guided by statistical analysis of prior data. We show that high-quality proteomics data provide crucial information to amend genome annotation and to confirm many predicted gene models. We also present experimentally identified proteotypic peptides matching approximately 50% of D. melanogaster gene models. This library of proteotypic peptides should enable fast, targeted and quantitative proteomic studies to elucidate the systems biology of this model organism.