TY  - JOUR
A1  - Ahmed, Zeeshan
A1  - Zeeshan, Saman
A1  - Huber, Claudia
A1  - Hensel, Michael
A1  - Schomburg, Dietmar
A1  - Münch, Richard
A1  - Eylert, Eva
A1  - Eisenreich, Wolfgang
A1  - Dandekar, Thomas
T1  - ‘Isotopo’ a database application for facile analysis and management of mass isotopomer data
JF  - Database
N2  - The composition of stable-isotope labelled isotopologues/isotopomers in metabolic products can be measured by mass spectrometry and supports the analysis of pathways and fluxes. As a prerequisite, the original mass spectra have to be processed, managed and stored to rapidly calculate, analyse and compare isotopomer enrichments to study, for instance, bacterial metabolism in infection. For such applications, we provide here the database application ‘Isotopo’. This software package includes (i) a database to store and process isotopomer data, (ii) a parser to upload and translate different data formats for such data and (iii) an improved application to process and convert signal intensities from mass spectra of \(^{13}C\)-labelled metabolites such as tertbutyldimethylsilyl-derivatives of amino acids. Relative mass intensities and isotopomer distributions are calculated applying a partial least square method with iterative refinement for high precision data. The data output includes formats such as graphs for overall enrichments in amino acids. The package is user-friendly for easy and robust data management of multiple experiments.
KW  - stable-isotope
Y1  - 2014
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-120102
VL  - 2014
IS  - bau077
ER  - 
TY  - JOUR
A1  - Ahmed, Zeeshan
A1  - Zeeshan, Saman
A1  - Dandekar, Thomas
T1  - Mining biomedical images towards valuable information retrieval in biomedical and life sciences
JF  - Database - The Journal of Biological Databases and Curation
N2  - Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries.
KW  - humans
KW  - software
KW  - image processing
KW  - animals
KW  - computer-assisted
KW  - data mining/methods
KW  - natural language processing
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-162697
VL  - 2016
ER  -