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Items: 33

1.

Stimulation augments spike sequence replay and memory consolidation during slow-wave sleep.

Wei Y, Krishnan GP, Marshall L, Martinetz T, Bazhenov M.

J Neurosci. 2019 Dec 2. pii: 1427-19. doi: 10.1523/JNEUROSCI.1427-19.2019. [Epub ahead of print]

PMID:
31792151
2.

Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition.

Alshazly H, Linse C, Barth E, Martinetz T.

Sensors (Basel). 2019 Sep 24;19(19). pii: E4139. doi: 10.3390/s19194139.

3.

A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation.

Schellenberger Costa M, Weigenand A, Ngo HV, Marshall L, Born J, Martinetz T, Claussen JC.

PLoS Comput Biol. 2016 Sep 1;12(9):e1005022. doi: 10.1371/journal.pcbi.1005022. eCollection 2016 Sep.

4.

Timing matters: open-loop stimulation does not improve overnight consolidation of word pairs in humans.

Weigenand A, Mölle M, Werner F, Martinetz T, Marshall L.

Eur J Neurosci. 2016 Sep;44(6):2357-68. doi: 10.1111/ejn.13334. Epub 2016 Aug 10.

5.

Modeling the effect of sleep regulation on a neural mass model.

Costa MS, Born J, Claussen JC, Martinetz T.

J Comput Neurosci. 2016 Aug;41(1):15-28. doi: 10.1007/s10827-016-0602-z. Epub 2016 Apr 11.

PMID:
27066796
6.

Correction: Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study.

Maier O, Schröder C, Forkert ND, Martinetz T, Handels H.

PLoS One. 2016 Feb 12;11(2):e0149828. doi: 10.1371/journal.pone.0149828. eCollection 2016. No abstract available.

7.

Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study.

Maier O, Schröder C, Forkert ND, Martinetz T, Handels H.

PLoS One. 2015 Dec 16;10(12):e0145118. doi: 10.1371/journal.pone.0145118. eCollection 2015. Erratum in: PLoS One. 2016;11(2):e0149828.

8.

RNAi revised--target mRNA-dependent enhancement of gene silencing.

Dornseifer S, Willkomm S, Far RK, Liebschwager J, Beltsiou F, Frank K, Laufer SD, Martinetz T, Sczakiel G, Claussen JC, Restle T.

Nucleic Acids Res. 2015 Dec 15;43(22):10623-32. doi: 10.1093/nar/gkv1200. Epub 2015 Nov 17.

9.

Driving sleep slow oscillations by auditory closed-loop stimulation-a self-limiting process.

Ngo HV, Miedema A, Faude I, Martinetz T, Mölle M, Born J.

J Neurosci. 2015 Apr 29;35(17):6630-8. doi: 10.1523/JNEUROSCI.3133-14.2015.

10.

EUROPattern Suite technology for computer-aided immunofluorescence microscopy in autoantibody diagnostics.

Krause C, Ens K, Fechner K, Voigt J, Fraune J, Rohwäder E, Hahn M, Danckwardt M, Feirer C, Barth E, Martinetz T, Stöcker W.

Lupus. 2015 Apr;24(4-5):516-29. doi: 10.1177/0961203314559635. Review.

PMID:
25801895
11.

Characterization of K-complexes and slow wave activity in a neural mass model.

Weigenand A, Schellenberger Costa M, Ngo HV, Claussen JC, Martinetz T.

PLoS Comput Biol. 2014 Nov 13;10(11):e1003923. doi: 10.1371/journal.pcbi.1003923. eCollection 2014 Nov.

12.

Auditory closed-loop stimulation of the sleep slow oscillation enhances memory.

Ngo HV, Martinetz T, Born J, Mölle M.

Neuron. 2013 May 8;78(3):545-53. doi: 10.1016/j.neuron.2013.03.006. Epub 2013 Apr 11.

13.

The support feature machine: classification with the least number of features and application to neuroimaging data.

Klement S, Anders S, Martinetz T.

Neural Comput. 2013 Jun;25(6):1548-84. doi: 10.1162/NECO_a_00447. Epub 2013 Mar 21.

PMID:
23517095
14.

Automated indirect immunofluorescence evaluation of antinuclear autoantibodies on HEp-2 cells.

Voigt J, Krause C, Rohwäder E, Saschenbrecker S, Hahn M, Danckwardt M, Feirer C, Ens K, Fechner K, Barth E, Martinetz T, Stöcker W.

Clin Dev Immunol. 2012;2012:651058. doi: 10.1155/2012/651058. Epub 2012 Nov 11.

15.

EcmPred: prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection.

Kandaswamy KK, Pugalenthi G, Kalies KU, Hartmann E, Martinetz T.

J Theor Biol. 2013 Jan 21;317:377-83. doi: 10.1016/j.jtbi.2012.10.015. Epub 2012 Nov 1.

PMID:
23123454
16.

The phase response of the cortical slow oscillation.

Weigenand A, Martinetz T, Claussen JC.

Cogn Neurodyn. 2012 Aug;6(4):367-75. doi: 10.1007/s11571-012-9207-z. Epub 2012 Jun 13.

17.

Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

Vig E, Dorr M, Martinetz T, Barth E.

IEEE Trans Pattern Anal Mach Intell. 2012 Jun;34(6):1080-91. doi: 10.1109/TPAMI.2011.198.

PMID:
22516647
18.

BLProt: prediction of bioluminescent proteins based on support vector machine and relieff feature selection.

Kandaswamy KK, Pugalenthi G, Hazrati MK, Kalies KU, Martinetz T.

BMC Bioinformatics. 2011 Aug 17;12:345. doi: 10.1186/1471-2105-12-345.

19.

PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome.

Zhang J, Mamlouk AM, Martinetz T, Chang S, Wang J, Hilgenfeld R.

BMC Bioinformatics. 2011 Jun 20;12:248. doi: 10.1186/1471-2105-12-248.

20.

AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties.

Kandaswamy KK, Chou KC, Martinetz T, Möller S, Suganthan PN, Sridharan S, Pugalenthi G.

J Theor Biol. 2011 Feb 7;270(1):56-62. doi: 10.1016/j.jtbi.2010.10.037. Epub 2010 Nov 4.

PMID:
21056045
21.

SMpred: a support vector machine approach to identify structural motifs in protein structure without using evolutionary information.

Pugalenthi G, Kandaswamy KK, Suganthan PN, Sowdhamini R, Martinetz T, Kolatkar PR.

J Biomol Struct Dyn. 2010 Dec;28(3):405-14.

PMID:
20919755
22.

Variability of eye movements when viewing dynamic natural scenes.

Dorr M, Martinetz T, Gegenfurtner KR, Barth E.

J Vis. 2010 Aug 26;10(10):28. doi: 10.1167/10.10.28.

PMID:
20884493
23.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

Kandaswamy KK, Pugalenthi G, Möller S, Hartmann E, Kalies KU, Suganthan PN, Martinetz T.

Protein Pept Lett. 2010 Dec;17(12):1473-9.

PMID:
20666727
24.

SPRED: A machine learning approach for the identification of classical and non-classical secretory proteins in mammalian genomes.

Kandaswamy KK, Pugalenthi G, Hartmann E, Kalies KU, Möller S, Suganthan PN, Martinetz T.

Biochem Biophys Res Commun. 2010 Jan 15;391(3):1306-11. doi: 10.1016/j.bbrc.2009.12.019. Epub 2009 Dec 6.

PMID:
19995554
25.

SoftDoubleMaxMinOver: perceptron-like training of support vector machines.

Martinetz T, Labusch K, Schneegass D.

IEEE Trans Neural Netw. 2009 Jul;20(7):1061-72. doi: 10.1109/TNN.2009.2016717. Epub 2009 Jun 2.

PMID:
19497817
26.

Adaptive dynamics of regulatory networks: size matters.

Repsilber D, Martinetz T, Björklund M.

EURASIP J Bioinform Syst Biol. 2009:618502. doi: 10.1155/2009/618502. Epub 2009 Mar 12.

27.

Simple method for high-performance digit recognition based on sparse coding.

Labusch K, Barth E, Martinetz T.

IEEE Trans Neural Netw. 2008 Nov;19(11):1985-9. doi: 10.1109/TNN.2008.2005830.

PMID:
19000969
28.

Binding matrix: a novel approach for binding site recognition.

Kim JT, Gewehr JE, Martinetz T.

J Bioinform Comput Biol. 2004 Jun;2(2):289-307.

PMID:
15297983
29.

Bioinformatic principles underlying the information content of transcription factor binding sites.

Kim JT, Martinetz T, Polani D.

J Theor Biol. 2003 Feb 21;220(4):529-44.

PMID:
12623284
30.

Adaptive walks on time-dependent fitness landscapes.

Wilke CO, Martinetz T.

Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1999 Aug;60(2 Pt B):2154-9.

PMID:
11970008
31.

Topology preservation in self-organizing feature maps: exact definition and measurement.

Villmann T, Der R, Herrmann M, Martinetz TM.

IEEE Trans Neural Netw. 1997;8(2):256-66.

PMID:
18255630
32.

;Neural-gas' network for vector quantization and its application to time-series prediction.

Martinetz TM, Berkovich SG, Schulten KJ.

IEEE Trans Neural Netw. 1993;4(4):558-69.

PMID:
18267757
33.

Three-dimensional neural net for learning visuomotor coordination of a robot arm.

Martinetz TM, Ritter HJ, Schulten KJ.

IEEE Trans Neural Netw. 1990;1(1):131-6.

PMID:
18282830

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