Biomedical subjects

Eunok Paek

Publications and source records attributed to Eunok Paek.

3 recordsLinked to original sources

PubMed2006

MODi: a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra.

MOD(i) (http://modi.uos.ac.kr/modi/) is a powerful and convenient web service that facilitates the interpretation of tandem mass spectra for identifying post-translational modifications (PTMs) in a peptide. It is powerful in that it can interpret a tandem mass spectrum even when hundreds of modification types are considered and the number of potential PTMs in a peptide is large, in contrast to most of the methods currently available for spectra interpretation that limit the number of PTM sites and types being used for PTM analysis. For example, using MOD(i), one can consider for analysis both the entire PTM list published on the unimod webpage (http://www.unimod.org) and user-defined PTMs simultaneously, and one can also identify multiple PTM sites in a spectrum. MOD(i) is convenient in that it can take various input file formats such as .mzXML, .dta, .pkl and .mgf files, and it is equipped with a graphical tool called MassPective developed to display MOD(i)'s output in a user-friendly manner and helps users understand MOD(i)'s output quickly. In addition, one can perform manual de novo sequencing using MassPective.

Computer Graphics↗

PubMed2006

Quality assessment of tandem mass spectra based on cumulative intensity normalization.

A large proportion of MS/MS spectral analyses do not result in significant matches because their spectral quality is too poor to produce meaningful identification. Throughput of peptide identification can be greatly improved, if one can filter out, in advance, spectra that would lead to wrong identification. We introduce here an innovative approach to assess spectral quality utilizing a new spectral feature called Xrea, based on cumulative intensity normalization.

Cell Line, Tumor↗

PubMed2004

Multi-layered representation for cell signaling pathways.

To understand complex signaling pathways and networks, it is necessary to develop a formal and structured representation of the available information in a format suitable for analysis by software tools. Due to the complexity and incompleteness of the current biological knowledge about cell signaling, such a device must be able to represent cellular pathways at differing levels of details, one level of information abstract enough to convey an essential signaling flow while hiding its details and another level of information detailed enough to explain the underlying mechanisms that account for the signaling flow described at a more abstract level. We have defined a formal ontology for cell-signaling events that allows us to describe these cellular pathways at various levels of abstraction. Using this formal representation, ROSPath (reactive oxygen species-mediated signaling pathway) database system has been implemented and made available on the web (rospath.ewha.ac.kr). ROSPath is a database system for reactive oxygen species (ROS)-mediated cell signaling pathways and signaling processes in molecular detail, which facilitates a comprehensive understanding of the regulatory mechanisms in signaling pathways. ROSPath includes growth factor-, stress-, and cytokine-induced signaling pathways containing about 500 unique proteins (mostly mammalian) and their related protein states, protein complexes, protein complex states, signaling interactions, signaling steps, and pathways. It is a web-based structured repository of information on the signaling pathways of interest and provides a means for managing data produced by large-scale and high-throughput techniques such as proteomics. Also, software tools are provided for querying, displaying, and analyzing pathways, thus furnishing an integrated web environment for visualizing and manipulating ROS-mediated cell-signaling events.

Cell Physiological Phenomena↗