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Items: 1 to 50 of 58

1.

On the impact of Citizen Science-derived data quality on deep learning based classification in marine images.

Langenkämper D, Simon-Lledó E, Hosking B, Jones DOB, Nattkemper TW.

PLoS One. 2019 Jun 12;14(6):e0218086. doi: 10.1371/journal.pone.0218086. eCollection 2019.

2.

Detection and visualization of communities in mass spectrometry imaging data.

Wüllems K, Kölling J, Bednarz H, Niehaus K, Hans VH, Nattkemper TW.

BMC Bioinformatics. 2019 Jun 4;20(1):303. doi: 10.1186/s12859-019-2890-6.

3.

Computer vision enables short- and long-term analysis of Lophelia pertusa polyp behaviour and colour from an underwater observatory.

Osterloff J, Nilssen I, Järnegren J, Van Engeland T, Buhl-Mortensen P, Nattkemper TW.

Sci Rep. 2019 Apr 29;9(1):6578. doi: 10.1038/s41598-019-41275-1.

4.

MAIA-A machine learning assisted image annotation method for environmental monitoring and exploration.

Zurowietz M, Langenkämper D, Hosking B, Ruhl HA, Nattkemper TW.

PLoS One. 2018 Nov 16;13(11):e0207498. doi: 10.1371/journal.pone.0207498. eCollection 2018.

5.

SeeVis-3D space-time cube rendering for visualization of microfluidics image data.

Hattab G, Nattkemper TW.

Bioinformatics. 2019 May 15;35(10):1802-1804. doi: 10.1093/bioinformatics/bty889.

6.

A Novel Methodology for Characterizing Cell Subpopulations in Automated Time-lapse Microscopy.

Hattab G, Wiesmann V, Becker A, Munzner T, Nattkemper TW.

Front Bioeng Biotechnol. 2018 Feb 28;6:17. doi: 10.3389/fbioe.2018.00017. eCollection 2018.

7.

ViCAR: An Adaptive and Landmark-Free Registration of Time Lapse Image Data from Microfluidics Experiments.

Hattab G, Schlüter JP, Becker A, Nattkemper TW.

Front Genet. 2017 May 31;8:69. doi: 10.3389/fgene.2017.00069. eCollection 2017.

8.

Omics Fusion - A Platform for Integrative Analysis of Omics Data.

Brink BG, Seidel A, Kleinbölting N, Nattkemper TW, Albaum SP.

J Integr Bioinform. 2016 Dec 18;13(4):296. doi: 10.2390/biecoll-jib-2016-296.

PMID:
28187412
9.

Computational Visual Stress Level Analysis of Calcareous Algae Exposed to Sedimentation.

Osterloff J, Nilssen I, Eide I, de Oliveira Figueiredo MA, de Souza Tâmega FT, Nattkemper TW.

PLoS One. 2016 Jun 10;11(6):e0157329. doi: 10.1371/journal.pone.0157329. eCollection 2016.

10.

Robust normalization protocols for multiplexed fluorescence bioimage analysis.

Ahmed Raza SE, Langenkämper D, Sirinukunwattana K, Epstein D, Nattkemper TW, Rajpoot NM.

BioData Min. 2016 Mar 5;9:11. doi: 10.1186/s13040-016-0088-2. eCollection 2016.

11.

Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging.

Gorzolka K, Kölling J, Nattkemper TW, Niehaus K.

PLoS One. 2016 Mar 3;11(3):e0150208. doi: 10.1371/journal.pone.0150208. eCollection 2016.

12.

Comparison of Acceleration Techniques for Selected Low-Level Bioinformatics Operations.

Langenkämper D, Jakobi T, Feld D, Jelonek L, Goesmann A, Nattkemper TW.

Front Genet. 2016 Feb 10;7:5. doi: 10.3389/fgene.2016.00005. eCollection 2016.

13.

Learning to Classify Organic and Conventional Wheat - A Machine Learning Driven Approach Using the MeltDB 2.0 Metabolomics Analysis Platform.

Kessler N, Bonte A, Albaum SP, Mäder P, Messmer M, Goesmann A, Niehaus K, Langenkämper G, Nattkemper TW.

Front Bioeng Biotechnol. 2015 Mar 24;3:35. doi: 10.3389/fbioe.2015.00035. eCollection 2015.

14.

AKE - the Accelerated k-mer Exploration web-tool for rapid taxonomic classification and visualization.

Langenkämper D, Goesmann A, Nattkemper TW.

BMC Bioinformatics. 2014 Dec 13;15:384. doi: 10.1186/s12859-014-0384-0.

15.

ALLocator: an interactive web platform for the analysis of metabolomic LC-ESI-MS datasets, enabling semi-automated, user-revised compound annotation and mass isotopomer ratio analysis.

Kessler N, Walter F, Persicke M, Albaum SP, Kalinowski J, Goesmann A, Niehaus K, Nattkemper TW.

PLoS One. 2014 Nov 26;9(11):e113909. doi: 10.1371/journal.pone.0113909. eCollection 2014.

16.

MeltDB 2.0-advances of the metabolomics software system.

Kessler N, Neuweger H, Bonte A, Langenkämper G, Niehaus K, Nattkemper TW, Goesmann A.

Bioinformatics. 2013 Oct 1;29(19):2452-9. doi: 10.1093/bioinformatics/btt414. Epub 2013 Aug 5.

17.

Categorization of two-photon microscopy images of human cartilage into states of osteoarthritis.

Bergmann T, Maeder U, Fiebich M, Dickob M, Nattkemper TW, Anselmetti D.

Osteoarthritis Cartilage. 2013 Aug;21(8):1074-82. doi: 10.1016/j.joca.2013.04.019. Epub 2013 May 13.

18.

Re-expression of IGF-II is important for beta cell regeneration in adult mice.

Zhou L, Pelengaris S, Abouna S, Young J, Epstein D, Herold J, Nattkemper TW, Nakhai H, Khan M.

PLoS One. 2012;7(9):e43623. doi: 10.1371/journal.pone.0043623. Epub 2012 Sep 7.

19.

Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN.

Schoening T, Bergmann M, Ontrup J, Taylor J, Dannheim J, Gutt J, Purser A, Nattkemper TW.

PLoS One. 2012;7(6):e38179. doi: 10.1371/journal.pone.0038179. Epub 2012 Jun 5.

20.

Protein turnover quantification in a multilabeling approach: from data calculation to evaluation.

Trötschel C, Albaum SP, Wolff D, Schröder S, Goesmann A, Nattkemper TW, Poetsch A.

Mol Cell Proteomics. 2012 Aug;11(8):512-26. doi: 10.1074/mcp.M111.014134. Epub 2012 Apr 6.

21.

WHIDE--a web tool for visual data mining colocation patterns in multivariate bioimages.

Kölling J, Langenkämper D, Abouna S, Khan M, Nattkemper TW.

Bioinformatics. 2012 Apr 15;28(8):1143-50. doi: 10.1093/bioinformatics/bts104. Epub 2012 Mar 5.

22.

RAMTaB: robust alignment of multi-tag bioimages.

Raza SE, Humayun A, Abouna S, Nattkemper TW, Epstein DB, Khan M, Rajpoot NM.

PLoS One. 2012;7(2):e30894. doi: 10.1371/journal.pone.0030894. Epub 2012 Feb 8.

23.

BioIMAX: a Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data.

Loyek C, Rajpoot NM, Khan M, Nattkemper TW.

BMC Bioinformatics. 2011 Jul 21;12:297. doi: 10.1186/1471-2105-12-297.

24.

Web2.0 paves new ways for collaborative and exploratory analysis of chemical compounds in spectrometry data.

Loyek C, Bunkowski A, Vautz W, Nattkemper TW.

J Integr Bioinform. 2011 Jul 18;8(2):158. doi: 10.2390/biecoll-jib-2011-158.

PMID:
21768655
25.

A guide through the computational analysis of isotope-labeled mass spectrometry-based quantitative proteomics data: an application study.

Albaum SP, Hahne H, Otto A, Haußmann U, Becher D, Poetsch A, Goesmann A, Nattkemper TW.

Proteome Sci. 2011 Jun 11;9:30. doi: 10.1186/1477-5956-9-30.

26.

Quantification of cell infection caused by Listeria monocytogenes invasion.

Arif M, Rajpoot NM, Nattkemper TW, Technow U, Chakraborty T, Fisch N, Jensen NA, Niehaus K.

J Biotechnol. 2011 Jun;154(1):76-83.

PMID:
21527293
27.

A Normalized Tree Index for identification of correlated clinical parameters in microarray experiments.

Martin CW, Tauchen A, Becker A, Nattkemper TW.

BioData Min. 2011 Jan 19;4(1):2. doi: 10.1186/1756-0381-4-2.

28.

Looking inside self-organizing map ensembles with resampling and negative correlation learning.

Scherbart A, Nattkemper TW.

Neural Netw. 2011 Jan;24(1):130-41. doi: 10.1016/j.neunet.2010.08.004. Epub 2010 Aug 27.

PMID:
20846822
29.

CellViCAM--Cell viability classification for animal cell cultures using dark field micrographs.

Burgemeister S, Nattkemper TW, Noll T, Hoffrogge R, Flaschel E.

J Biotechnol. 2010 Sep 15;149(4):310-6. doi: 10.1016/j.jbiotec.2010.07.020. Epub 2010 Jul 23.

PMID:
20655961
30.

Automated detection and quantification of fluorescently labeled synapses in murine brain tissue sections for high throughput applications.

Herold J, Schubert W, Nattkemper TW.

J Biotechnol. 2010 Sep 15;149(4):299-309. doi: 10.1016/j.jbiotec.2010.03.004. Epub 2010 Mar 15.

PMID:
20230863
31.

Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue.

Herold J, Zhou L, Abouna S, Pelengaris S, Epstein D, Khan M, Nattkemper TW.

Comput Med Imaging Graph. 2010 Sep;34(6):446-52. doi: 10.1016/j.compmedimag.2009.10.004. Epub 2009 Dec 6.

PMID:
19969439
32.

Qupe--a Rich Internet Application to take a step forward in the analysis of mass spectrometry-based quantitative proteomics experiments.

Albaum SP, Neuweger H, Fränzel B, Lange S, Mertens D, Trötschel C, Wolters D, Kalinowski J, Nattkemper TW, Goesmann A.

Bioinformatics. 2009 Dec 1;25(23):3128-34. doi: 10.1093/bioinformatics/btp568. Epub 2009 Oct 6.

PMID:
19808875
33.

Model-Free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning.

Twellmann T, Meyer-Baese A, Lange O, Foo S, Nattkemper TW.

Eng Appl Artif Intell. 2008 Mar;21(2):129-140.

34.

TACOA: taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach.

Diaz NN, Krause L, Goesmann A, Niehaus K, Nattkemper TW.

BMC Bioinformatics. 2009 Feb 11;10:56. doi: 10.1186/1471-2105-10-56.

35.

A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification.

Wei N, Flaschel E, Friehs K, Nattkemper TW.

BMC Bioinformatics. 2008 Oct 21;9:449. doi: 10.1186/1471-2105-9-449.

36.

Peak intensity prediction in MALDI-TOF mass spectrometry: a machine learning study to support quantitative proteomics.

Timm W, Scherbart A, Böcker S, Kohlbacher O, Nattkemper TW.

BMC Bioinformatics. 2008 Oct 20;9:443. doi: 10.1186/1471-2105-9-443.

37.

Hyperbolic SOM-based clustering of DNA fragment features for taxonomic visualization and classification.

Martin C, Diaz NN, Ontrup J, Nattkemper TW.

Bioinformatics. 2008 Jul 15;24(14):1568-74. doi: 10.1093/bioinformatics/btn257. Epub 2008 Jun 5.

PMID:
18535082
38.

Phylogenetic classification of short environmental DNA fragments.

Krause L, Diaz NN, Goesmann A, Kelley S, Nattkemper TW, Rohwer F, Edwards RA, Stoye J.

Nucleic Acids Res. 2008 Apr;36(7):2230-9. doi: 10.1093/nar/gkn038. Epub 2008 Feb 19.

39.

Identification of genes relevant to symbiosis and competitiveness in Sinorhizobium meliloti using signature-tagged mutants.

Pobigaylo N, Szymczak S, Nattkemper TW, Becker A.

Mol Plant Microbe Interact. 2008 Feb;21(2):219-31. doi: 10.1094/MPMI-21-2-0219.

40.

Multiscale analysis of MR-mammography data.

Lessmann B, Nattkemper TW, Kessar P, Pointon L, Khazen M, Leach MO, Degenhard A.

Z Med Phys. 2007;17(3):166-71.

PMID:
17879813
41.

A method for linking computed image features to histological semantics in neuropathology.

Lessmann B, Nattkemper TW, Hans VH, Degenhard A.

J Biomed Inform. 2007 Dec;40(6):631-41. Epub 2007 Jul 5.

42.

Reagent-free automatic cell viability determination using neural networks based machine vision and dark-field microscopy in Saccharomyces cerevisiae.

Wei N, Flaschel E, Saalbach A, Twellmann T, Nattkemper TW.

Conf Proc IEEE Eng Med Biol Soc. 2005;6:6305-8.

PMID:
17281709
43.
44.

Detection of suspicious lesions in dynamic contrast enhanced MRI data.

Twellmann T, Saalbach A, Müller C, Nattkemper TW, Wismüller A.

Conf Proc IEEE Eng Med Biol Soc. 2004;1:454-7.

PMID:
17271711
45.

In situ dark field microscopy for on-line monitoring of yeast cultures.

Wei N, You J, Friehs K, Flaschel E, Nattkemper TW.

Biotechnol Lett. 2007 Mar;29(3):373-8. Epub 2006 Dec 21.

PMID:
17186133
46.

GISMO--gene identification using a support vector machine for ORF classification.

Krause L, McHardy AC, Nattkemper TW, Pühler A, Stoye J, Meyer F.

Nucleic Acids Res. 2007;35(2):540-9. Epub 2006 Dec 14.

47.

Construction of a large signature-tagged mini-Tn5 transposon library and its application to mutagenesis of Sinorhizobium meliloti.

Pobigaylo N, Wetter D, Szymczak S, Schiller U, Kurtz S, Meyer F, Nattkemper TW, Becker A.

Appl Environ Microbiol. 2006 Jun;72(6):4329-37.

48.

An adaptive tissue characterization network for model-free visualization of dynamic contrast-enhanced magnetic resonance image data.

Twellmann T, Lichte O, Nattkemper TW.

IEEE Trans Med Imaging. 2005 Oct;24(10):1256-66.

PMID:
16229413
49.

Machine learning approaches for phenotype-genotype mapping: predicting heterozygous mutations in the CYP21B gene from steroid profiles.

Prank K, Schulze E, Eckert O, Nattkemper TW, Bettendorf M, Maser-Gluth C, Sejnowski TJ, Grote A, Penner E, von Zur Mühlen A, Brabant G.

Eur J Endocrinol. 2005 Aug;153(2):301-5.

50.

Libraries of synthetic stationary-phase and stress promoters as a tool for fine-tuning of expression of recombinant proteins in Escherichia coli.

Miksch G, Bettenworth F, Friehs K, Flaschel E, Saalbach A, Twellmann T, Nattkemper TW.

J Biotechnol. 2005 Oct 17;120(1):25-37. Epub 2005 Jul 12.

PMID:
16019099

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