Literature DB >> 15916558

Location proteomics: a systems approach to subcellular location.

R F Murphy1.   

Abstract

Systems Biology requires comprehensive systematic data on all aspects and levels of biological organization and function. In addition to information on the sequence, structure, activities and binding interactions of all biological macromolecules, the creation of accurate predictive models of cell behaviour will require detailed information on the distribution of those molecules within cells and the ways in which those distributions change over the cell cycle and in response to mutations or external stimuli. Current information on subcellular location in protein databases is limited to unstructured text descriptions or sets of terms assigned by human curators. These entries do not permit basic operations that are common to other biological databases, such as measurement of the degree of similarity between the distributions of two proteins, and they are not able to fully capture the complexity of protein patterns that can be observed. The field of location proteomics seeks to provide automated, objective high-resolution descriptions of protein location patterns within cells. Methods have been developed to group proteins into statistically indistinguishable location patterns using automated analysis of fluorescence microscope images. The resulting clusters, or location families, are analogous to clusters found for other domains, such as protein sequence families. Preliminary work suggests the feasibility of expressing each unique pattern as a generative model that can be incorporated into comprehensive models of cell behaviour.

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Year:  2005        PMID: 15916558     DOI: 10.1042/BST0330535

Source DB:  PubMed          Journal:  Biochem Soc Trans        ISSN: 0300-5127            Impact factor:   5.407


  11 in total

Review 1.  Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics.

Authors:  Xiang Chen; Meel Velliste; Robert F Murphy
Journal:  Cytometry A       Date:  2006-07       Impact factor: 4.355

Review 2.  New gateways to discovery.

Authors:  Michael M Goodin; Romit Chakrabarty; Rituparna Banerjee; Sharon Yelton; Seth Debolt
Journal:  Plant Physiol       Date:  2007-12       Impact factor: 8.340

3.  Model building and intelligent acquisition with application to protein subcellular location classification.

Authors:  C Jackson; E Glory-Afshar; R F Murphy; J Kovacevic
Journal:  Bioinformatics       Date:  2011-05-09       Impact factor: 6.937

4.  PMLPR: A novel method for predicting subcellular localization based on recommender systems.

Authors:  Elnaz Mirzaei Mehrabad; Reza Hassanzadeh; Changiz Eslahchi
Journal:  Sci Rep       Date:  2018-08-13       Impact factor: 4.379

5.  Prospecting for Live Cell BioImaging Probes With Cheminformatic Assisted Image Arrays (CAIA).

Authors:  Kerby Shedden; Maria M Posada; Young Tae Chang; Qian Li; Gus Rosania
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2007

6.  Machine vision-assisted analysis of structure-localization relationships in a combinatorial library of prospective bioimaging probes.

Authors:  Kerby Shedden; Qian Li; Fangyi Liu; Young Tae Chang; Gus R Rosania
Journal:  Cytometry A       Date:  2009-06       Impact factor: 4.355

7.  Chemical address tags of fluorescent bioimaging probes.

Authors:  Kerby Shedden; Gus R Rosania
Journal:  Cytometry A       Date:  2010-05       Impact factor: 4.355

8.  Beyond captions: linking figures with abstract sentences in biomedical articles.

Authors:  Joseph P Bockhorst; John M Conroy; Shashank Agarwal; Dianne P O'Leary; Hong Yu
Journal:  PLoS One       Date:  2012-07-18       Impact factor: 3.240

9.  Predicted mouse peroxisome-targeted proteins and their actual subcellular locations.

Authors:  Yumi Mizuno; Igor V Kurochkin; Marlis Herberth; Yasushi Okazaki; Christian Schönbach
Journal:  BMC Bioinformatics       Date:  2008-12-12       Impact factor: 3.169

10.  LOCATE: a mammalian protein subcellular localization database.

Authors:  Josefine Sprenger; J Lynn Fink; Seetha Karunaratne; Kelly Hanson; Nicholas A Hamilton; Rohan D Teasdale
Journal:  Nucleic Acids Res       Date:  2007-11-05       Impact factor: 16.971

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