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  - 
TY  - JOUR
A1  - Karulin, Alexey Y.
A1  - Karacsony, Kinga
A1  - Zhang, Wenji
A1  - Targoni, Oleg S.
A1  - Moldova, Ioana
A1  - Dittrich, Marcus
A1  - Sundararaman, Srividya
A1  - Lehmann, Paul V.
T1  - ELISPOTs produced by CD8 and CD4 cells follow Log Normal size distribution permitting objective counting
JF  - Cells
N2  - Each positive well in ELISPOT assays contains spots of variable sizes that can range from tens of micrometers up to a millimeter in diameter. Therefore, when it comes to counting these spots the decision on setting the lower and the upper spot size thresholds to discriminate between non-specific background noise, spots produced by individual T cells, and spots formed by T cell clusters is critical. If the spot sizes follow a known statistical distribution, precise predictions on minimal and maximal spot sizes, belonging to a given T cell population, can be made. We studied the size distributional properties of IFN-γ, IL-2, IL-4, IL-5 and IL-17 spots elicited in ELISPOT assays with PBMC from 172 healthy donors, upon stimulation with 32 individual viral peptides representing defined HLA Class I-restricted epitopes for CD8 cells, and with protein antigens of CMV and EBV activating CD4 cells. A total of 334 CD8 and 80 CD4 positive T cell responses were analyzed. In 99.7% of the test cases, spot size distributions followed Log Normal function. These data formally demonstrate that it is possible to establish objective, statistically validated parameters for counting T cell ELISPOTs.
KW  - ELISPOT
KW  - software
KW  - IFN-γ
KW  - IL-17
KW  - T cells
KW  - Normal Distribution
KW  - spot size
KW  - gating
KW  - cytokines
KW  - IL-2
KW  - IL-4
KW  - IL-5
KW  - CD8
KW  - CD4
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-149648
VL  - 4
IS  - 1
ER  -