Algorithms for Compound Identification by Mass Spectrometry

NIST, United States

Updated: about 14 hours ago
Location: Gaithersburg, MARYLAND

RAP opportunity at National Institute of Standards and Technology     NIST

Algorithms for Compound Identification by Mass Spectrometry


Location

Material Measurement Laboratory, Biomolecular Measurement Division


opportunity location
50.64.51.B8162 Gaithersburg, MD

NIST only participates in the February and August reviews.


Advisers
name email phone
Xiaoyu Yang xiaoyu.yang@nist.gov 301.975.2501
Description

The translation of a mass spectrum into a chemical identification is often a very imprecise and error prone part of the rapidly expanding fields of mass spectrometry-based proteomics and metabolomics. Our studies focus on developing new mass spectral data analysis algorithms (e.g., clustering) to better solve the common key persistent problems arising from factors such as mass shift and peak intensity variation; noise perception and removal, and ambiguous identifications. We are interested now in exploring the techniques to tackle the problems associated with fragmentation pathway or structure-spectrum correlation from MSn (MS2, MS3, and MS4) spectra. Available resources include NIST Tandem Mass Spectral Library and terabytes of mass spectral data that are stored at our mass spectrometry data center. Applicants are expected to be skilled in one of the programming language such as C++/C, Perl, Matlab, or R, and have majored in Chemistry, Statistics, or Computer Science.

Reference

Yang X, et al: Analytical Chemistry 86(13): 6393-6400, 2014


key words

Mass spectrometry; Data analysis; Algorithm; Clustering; MS/MS; Proteomics; Metabolomics; Compound identification; Data mining;


Eligibility

citizenship

Open to U.S. citizens


level

Open to Postdoctoral applicants


Stipend
Base Stipend Travel Allotment Supplementation
$82,764.00 $3,000.00

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