Thomas Martinetz

Research output

Research Output per year 2010 2010 2011 2012 2013 2014 2015 2016 2024

• 58 Journal articles
• 37 Conference contribution
• 2 Conference proceedings
• 2 Conference Papers
• 6 More
  • 1 Chapter
  • 1 Comments/Debates
  • 1 Conference Articles in Journals
  • 1 Editorial
  • 1 Contributions to academic memorandum
  • 1 Working papers

Research Output per year

Research Output per year

Search results

• 2014

  Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

  Weigenand, A., Schellenberger Costa, M., Ngo, H. V. V., Claussen, J. C. & Martinetz, T., 13.11.2014, In: PLoS Computational Biology. 10, 11, p. 1-10 10 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Model 100%
  • Oscillatory Motion 100%
  • Points 100%
  • Stages 75%
  • Behavior (Neuroscience) 50%
  4 Citations (Scopus)

• Committees of deep feedforward networks trained with few data

  Miclut, B., Kaester, T., Martinetz, T. & Barth, E., 23.06.2014, In: arXiv.org. 7 p.

  Research output: Journal Articles › Journal articles › Research

  • classification result 50%
  • Classification Task 50%

• Global Metric Learning by Gradient Descent

  Hocke, J. & Martinetz, T., 01.01.2014, Artificial Neural Networks and Machine Learning - ICANN 2014. Wermter, S., Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P., Magg, S., Palm, G. & Villa, A. E. P. (eds.). 1 ed. Springer Verlag, p. 129-135 7 p. (Theoretical Computer Science and General Issues; vol. 8681).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Classifier 50%

• Key-point Detection with Multi-layer Center-surround Inhibition

  Coleca, F., Zîrnovean, S., Käster, T., Martinetz, T. & Barth, E., 01.01.2014, Proceedings of the 9th International Conference on Computer Vision Theory and Application. Battiato, S. (ed.). 1 ed. Lisbon, Portugal: SciTePress, Vol. Vol. 1. p. 386-393 8 p. (INSTICC Conference Proceedings).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Dataset 50%
  • Algorithm 50%
  • Density 50%
  • Detection Algorithm 50%
  • Keypoints 50%

• Learning and modelling big data

  Hammer, B., He, H. & Martinetz, T., 17.03.2014, ESANN 2014. ESANN, p. 343-352 10 p. ES2014-8. (ESANN: The European Symposium on Artificial Neural Networks ).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Machine Learning 100%
  • Data Type 49%
  • Machine Learning Approach 49%
  • Paradigm Shift 49%
  • Assumption 49%

• Learning Transformation Invariance for Object Recognition

  Hocke, J. & Martinetz, T., 02.09.2014, Workshop New Challenges in Neural Computation 2014. Hammer, B. & Villmann, T. (eds.). Vol. 02. p. 20-25 6 p. (Machine Learning Reports).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Transformation 100%

• Maximum distance minimization for feature weighting

  Hocke, J. & Martinetz, T., 15.01.2014, In: Pattern Recognition Letters. 52, p. 48-52 5 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  3 Citations (Scopus)

• Proceedings, Student Conference 2014, Medical Engineering Science

  Buzug, T. M., Birngruber, R., Botterweck, H., Brinkmann, R., Gehring, H., Handels, H., Hellbrück, H., Hübner, C., Hüttmann, G., Klein, S., Koch, M., Leucker, M., Linz, N., Mamlouk, A. M., Martinetz, T., Mertins, A., Müller, S., Nestler, B., Paulsen, H. & Ryschka, M. & 3 others, Schulz, A.-P., Schweikard, A. & Rahmanzadeh, R., 25.02.2014, Lübeck: Grin Verlag. 296 p. (Student Conference on Medical Engineering Science)

  Research output: Books/Anthologies/Proceedings/Theses › Conference proceedings › Research

  • University 66%
  • Students 66%

• Visual Manifold Sensing

  Burciu, I., Ion-Margineanu, A., Martinetz, T. & Barth, E., 25.02.2014, Human Vision and Electronic Imaging XIX. Rogowitz, B. E., Pappas, T. N. & de Ridder, H. (eds.). SPIE, Vol. 90141B . p. 9014 - 9014 - 8 8 p. (Proceedings of SPIE; vol. 9014).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Detection 100%
  • Dataset 20%
• 2013

  ANA and ANCA diagnostics with computer-aided immunofluorescence microscopy (CAIFM)

  Hochstrate, N., Krause, C., Ens, K., Danckwardt, M., Feirer, C., Rohwäder, E., Hahn, M., Affeldt, K., Rateike, M., Morrin, M., Wuttig, D., Fechner, K., Barth, E., Stöcker, W., Martinetz, T. & Voigt, J., 09.2013, In: Zeitschrift fur Rheumatologie. 72, 2, p. 24 1 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Immunofluorescence Microscopy 100%

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

  Ngo, H. V. V., Martinetz, T., Born, J. & Mölle, M., 08.05.2013, In: Neuron. 78, 3, p. 545-553 9 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Slow Oscillation 100%
  • Brain 33%
  • Sleep Pattern 33%
  • Memory Consolidation 33%
  • Declarative Memory 33%
  152 Citations (Scopus)

• Computer-aided immunofluorescence microscopy (CAIFM) for ANCA diagnostics

  Hochstrate, N., Krause, C., Ens, K., Danckwardt, M., Feirer, C., Affeldt, K., Rateike, M., Morrin, M., Wuttig, D., Voigt, J., Fechner, K., Barth, E., Martinetz, T. & Stöcker, W., 04.2013, In: Presse Medicale. 42, 4, p. 685 1 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Immunofluorescence Microscopy 100%
  • Neutrophil 100%
  • Computer 100%
  • Microscopy 100%
  • Immunofluorescence 100%

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

  Kandaswamy, K. K., Pugalenthi, G., Kalies, K. U., Hartmann, E. & Martinetz, T., 01.01.2013, In: Journal of Theoretical Biology. 317, p. 377-383 7 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Random Forest 100%
  • Extracellular Matrix Proteins 100%
  • Training 16%
  • Macromolecule 16%
  • Polysaccharide 16%
  9 Citations (Scopus)

• Feature Weighting by Maximum Distance Minimization

  Hocke, J. & Martinetz, T., 08.10.2013, Artificial Neural Networks and Machine Learning – ICANN 2013: 23rd International Conference on Artificial Neural Networks Sofia, Bulgaria, September 10-13, 2013. Proceedings. Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A. E. P., Appollini, B. & Kasabov, N. (eds.). Springer Berlin Heidelberg, Vol. Vol. 8131. p. 420-425 6 p. (Lecture Notes in Computer Science; vol. Vol. 8131).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Algorithms 100%
  • Learning Algorithm 50%

• Gesture Interfaces with Depth Sensors

  Coleca, F., Martinetz, T. & Barth, E., 01.01.2013, Time-of-Flight and Depth Imaging. Sensors, Algorithms and Applications: Dagstuhl Seminar 2012 and GCPR Workshop on Imaging New Modalities. Grzegorzek, M., Theobalt, C., Koch, R. & Kolb, A. (eds.). 1 ed. Springer Berlin Heidelberg, Vol. 8200. p. 207-227 20 p. (Lecture Notes in Computer Science).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Complexity 100%
  • Algorithms 50%
  • Computer 50%
  • Computer Hardware 50%

• Hand Tracking with an Extended Self-Organizing Map

  State, A., Coleca, F., Barth, E. & Martinetz, T., 2013, Advances in Self-Organizing Maps. Estévez, P. A., Príncipe, J. C. & Zegers, P. (eds.). Springer Berlin Heidelberg, Vol. Vol. 198. p. 115-124 10 p. (Advances in Intelligent Systems and Computing ; vol. Vol. 198).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Algorithms 50%
  • Data Collection 50%

• Learning Orthogonal Bases for k-Sparse Representations

  Schütze, H., Barth, E. & Martinetz, T., 2013, Workshop New Challenges in Neural Computation 2013. Hammer, B., Martinetz, T. & Villmann, T. (eds.). Vol. 02. p. 119-120 2 p. (Machine Learning Reports).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Sample 100%
  • Projection 50%

• Optimizing depth-of-field based on a range map and a wavelet transform

  Wellner, M., Kastera, T., Martinetz, T. & Barth, E., 01.03.2013, Multimedia Content and Mobile Devices . SPIE, Vol. 86671U . p. 8667 - 8667 - 8 8 p. (Proceedings of SPIE ; vol. 8667).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Wavelet 100%
  • Image 50%
  • Need 33%
  • Edge 20%
  • Image Processing 20%

• Real-time skeleton tracking for embedded systems

  Coleca, F., Klement, S., Martinetz, T. & Barth, E., 26.03.2013, Multimedia Content and Mobile Devices. SPIE, Vol. 8667. p. 8667 - 8667 - 8 8 p. (Proceedings of SPIE; vol. 8667).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Algorithms 100%
  • Detection 40%
  • Segmentation 20%
  • Artifact 20%
  • Graphics Processing Unit 20%

• Sparse Coding Neural Gas Applied to Image Recognition

  Coman, H., Barth, E. & Martinetz, T., 01.01.2013, Advances in Self-Organizing Maps: 9th Workshop on Self-Organizing Maps. Estévez, P. A., Príncipe, J. C. & Zegers, P. (eds.). Springer Berlin Heidelberg, p. 105-114 10 p. (Advances in Intelligent Systems and Computing; vol. Vol. 198).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Dataset 100%
  • Algorithm 100%
  • Sparse Coding 100%
  • Algorithms 100%
  • State-of-the-Art Method 50%

• The Support Vector Machine: Classification with the Least Number of Features and Application to Neuroimaging Data

  Klement, S., Anders, S. & Martinetz, T., 21.05.2013, In: Neural Computation. 25, 6, p. 1548-1584 37 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Number 100%
  • Application 100%
  • Selection 100%
  • Feature Selection 100%
  • Procedure 33%
  3 Citations (Scopus)
• 2012

  A Multivariate Approach to Estimate Complexity of FMRI Time Series

  Schütze, H., Martinetz, T., Anders, S. & Mamlouk, A. M., 2012, Artificial Neural Networks and Machine Learning - ICANN 2012, 22nd International Conference, Lausanne, Switzerland, September 11-14, 2012, Proceedings, Part II. Villa, A. E. P., Duch, W., Érdi, P., Masulli, F. & Palm, G. (eds.). Springer Verlag, Vol. 7553. p. 540-547 8 p. (Lecture Notes in Computer Science; vol. 7553).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Functional Magnetic Resonance Imaging 100%
  • Complexity 100%
  • Brain 25%
  • Brain Imaging 25%
  • Analysis Method 16%

• A physical theory of economic growth

  Danielmeyer, H. G. & Martinetz, T., 12.06.2012, In: arXiv:1206.2494v1 [q-fin.GN]. 14 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Economics 100%
  • Supply 50%
  • Problem 33%
  • Information 33%
  • Nation 33%

• Application of non-linear transform coding to image processing

  Hocke, J., Barth, E. & Martinetz, T., 10.02.2012, Human Vision and Electronic Imaging XVII. Rogowitz, B. E., Pappas, T. N. & de Ridder, H. (eds.). SPIE, Vol. 8291. 829105. (Proceedings of SPIE; vol. 8291).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Algorithms 100%
  • Image Processing 100%
  • Approximation (Algorithm) 50%
  • Algorithm 50%
  • Sparse Coding 25%

• 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., 18.10.2012, In: Clinical and Developmental Immunology. 2012, 7 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

• How to make a small phone camera shoot like a big DSLR: creating and fusing multi-modal exposure series

  Binder, T., Kriener, F., Wichner, C., Wille, M., Wellner, M., Kaester, T., Martinetz, T. & Barth, E., 09.03.2012, Human Vision and Electronic Imaging XVII. Rogowitz, B. E., Pappas, T. N. & de Ridder , H. (eds.). SPIE, Vol. 8291. p. 8291 - 8291 - 10 10 p. (Proceedings of SPIE; vol. 8291).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • High Quality 33%
  • Exposure Time 33%

• Intrinsic Dimensionality Predicts the Saliency of Natural Dynamic Scenes

  Vig, E., Dorr, M., Martinetz, T. & Barth, E., 06.2012, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 34, 6, p. 1080-1091 12 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Complexity 66%
  • Learning System 33%
  • Machine Learning 33%
  • Signal Processing 33%

• On the boundedness of an iteration involving points on the hypersphere

  Binder, T. & Martinetz, T., 01.12.2012, In: International Journal of Computational Geometry and Applications. 22, 6, p. 499-515 17 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Points 100%

• Predicting economic growth with classical physics and human biology

  Danielmeyer, H. G. & Martinetz, T., 06.12.2012, In: arXiv:1212.1286 [q-fin.GN]. 4 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Growth 100%
  • Output 100%
  • Analytics 50%
  • Infrastructure 50%
  • Recovery 50%

• Sparse Coding and Selected Applications

  Hocke, J., Labusch, K., Barth, E. & Martinetz, T., 09.05.2012, KI - Künstliche Intelligenz. p. 349-355 7 p. (KI - Künstliche Intelligenz; vol. 26).

  Research output: Chapters in Books/Reports/Conference Proceedings › Chapter › peer-review

  • Motivation 100%
  • Gas 66%
  • image feature 50%
  • Signal Processing 50%
  • Reconstruction 33%

• The phase response of the cortical slow oscillation

  Weigenand, A., Martinetz, T. & Claussen, J. C., 13.06.2012, In: Cognitive Neurodynamics. 6, 4, p. 367-375 9 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Electrotherapy 100%
  • Oscillatory Motion 100%
  • Slow Oscillation 100%
  • Rapid Eye Movement Sleep 25%
  • Brain 25%

• The physics of business cycles and inflation

  Danielmeyer, H. G. & Martinetz, T., 2012, In: arXiv:1212.1282v1 [q-fin.GN]. 3 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Inflation 100%
  • Business Cycle 100%
  • Lotka-Volterra Equation 100%
  • Cycle 100%
  • Interest Rate 50%
• 2011

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

  Kandaswamy, K. K., Chou, K.-C., Martinetz, T., Möller, S., Suganthan, P. N., Sridharan, S. & Pugalenthi, G., 07.02.2011, In: Journal of Theoretical Biology. 270, 1, p. 56-62 7 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Random Forest 100%
  • Plant-Based Food 100%
  • Temperature 50%
  • Vertebra 50%
  • Fungus 50%

• BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

  Kandaswamy, K. K., Pugalenthi, G., Hazrati, M. K., Kalies, K. U. & Martinetz, T., 17.08.2011, In: BMC Bioinformatics. 12, 7 p., 345.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Protein 100%
  • Support Vector Machine 100%
  • Light 25%
  • Training 8%
  17 Citations (Scopus)

• Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes

  Vig, E., Dorr, M., Martinetz, T. & Barth, E., 14.08.2011, In: Cognitive Computation. 3, 1, p. 79-88 10 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Eye Movement 100%
  • Research 20%
  • Attention 20%
  • Correlation Analysis 20%

• Image Deconvolution with Sparse Priors

  Hocke, J., Martinetz, T. & Barth, E., 16.08.2011, Workshop New Challenges in Neural Computation 2011. Hammer, B. & Villmann, T. (eds.). Vol. 05. p. 9 - 9 1 p. (Machine Learning Reports).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Designation of Origin 100%
  • Model 25%
  • Limitations 25%
  • Sparse Coding 25%

• On the Problem of Finding the Least Number of Features by L1-norm Minimisation

  Klement, S. & Martinetz, T., 2011, Artificial Neural Networks and Machine Learning – ICANN 2011. Honkela, T., Duch, W., Girolami, M. & Kaski, S. (eds.). Springer Berlin Heidelberg, Vol. 6791. p. 315-322 8 p. (Lecture Notes in Computer Science; vol. 6791).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Number 100%
  • Feature Selection 100%
  • Selection 50%
  • Data Point 50%

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

  Zhang, J., Mamlouk, A. M., Martinetz, T., Chang, S., Wang, J. & Hilgenfeld, R., 20.06.2011, In: BMC Bioinformatics. 12, 1, p. 248-266 19 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Gene 16%
  • Database 16%
  4 Citations (Scopus)

• Robust and Fast Learning of Sparse Codes With Stochastic Gradient Descent

  Labusch, K., Barth, E. & Martinetz, T., 09.2011, In: IEEE Journal of Selected Topics in Signal Processing. 5, 5, p. 1048-1060 13 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Direction 100%
  • Sample 50%
  • Algorithms 40%
  • Powerful Method 33%
  • Elements 33%

• Soft-competitive Learning of Sparse Codes and its Application to Image Reconstruction

  Labusch, K., Barth, E. & Martinetz, T., 01.04.2011, In: Neurocomputing. 74, 9, p. 1418-1428 11 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Algorithm 100%
  • Image Reconstruction 100%
  • Algorithms 83%
  • Experiment 20%
  • Sparse Coding 20%
• 2010

  A Learned Saliency Predictor for Dynamic Natural Scenes

  Vig, E., Dorr, M., Martinetz, T. & Barth, E., 2010, Artificial Neural Networks -- ICANN 2010. Diamantaras, K., Duch, W. & Iliadis, L. S. (eds.). Berlin, Heidelberg: Springer Berlin Heidelberg, Vol. 6354. p. 52-61 10 p. (Lecture Notes in Computer Science; vol. 6354).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Classifier 100%

• A new approach to classification with the least number of features

  Klement, S. & Martinetz, T., 28.12.2010, Proceedings of the 9th International Conference on Machine Learning and Applications - ICMLA 2010, Washington, D.C, USA, 12--14 December, 2010. IEEE, p. 141-146 6 p. (Proceedings of the IEEE).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Complexity 100%
  • Learning System 100%
  • Identification 100%
  • Machine Learning 100%
  • classification result 100%

• Bag of Pursuits and Neural Gas for Improved Sparse Coding

  Labusch, K., Barth, E. & Martinetz, T., 01.2010, Proceedings of COMPSTAT'2010. Lechevallier, Y. & Saporta, G. (eds.). Heidelberg: Physica-Verlag HD, p. 327-336 10 p.

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Algorithms 50%
  • Approximation (Algorithm) 50%

• Interpretive Risk Assessment on GWA Data with Sparse Linear Regression

  Brænne, I., Labusch, K., Martinetz, T. & Mamlouk, A. M., 2010, In: Machine Learning Reports. p. 61-68 8 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Wide Association Study 100%
  • Classifier 100%
  • Number 100%
  • Prediction 100%
  • Algorithms 50%

• Learning Sparse Codes for Image Reconstruction

  Labusch, K. & Martinetz, T., 04.2010, Proceedings of the 18th European Symposium on Artificial Neural Networks. Verleysen, M. (ed.). ESANN, p. 241-246 6 p.

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Algorithm 100%
  • Image Reconstruction 100%
  • Algorithms 100%
  • Sparse Coding 50%
  • Elements 25%

• Optical Inspection of Welding Seams

  Timm, F., Martinetz, T. & Barth, E., 2010, Computer Vision, Imaging and Computer Graphics. Theory and Applications. Ranchordas, A., Pereira, J. M., Araújo, H. J. & Tavares, J. M. R. S. (eds.). Berlin, Heidelberg: Springer Berlin Heidelberg, Vol. 68. p. 269-282 14 p. (Communications in Computer and Information Science; vol. 68).

  Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

  • Geometry 100%
  • Support Vector Machine 100%

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

  Kandaswamy, K. K., Pugalenthi, G., Möller, S., Hartmann, E., Kalies, K. U., Suganthan, P. N. & Martinetz, T., 01.12.2010, In: Protein and Peptide Letters. 17, 12, p. 1473-1479 7 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Protein 100%
  • Programmed Cell Death 100%
  • Support Vector Machine 100%
  • Cell Death 50%
  • Homeostasis 16%
  78 Citations (Scopus)

• Shading constraint improves accuracy of time-of-flight measurements

  Böhme, M., Haker, M., Martinetz, T. & Barth, E., 01.12.2010, In: Computer Vision and Image Understanding. 114, 12, p. 1329-1335 7 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Image 100%
  • Albedo 40%
  • Show 20%
  • Real Time 20%
  • Property 20%
  20 Citations (Scopus)

• Smpred: A support vector machine approach to identify structural motifs in protein structure without using evolutionary information

  Pugalenthi, G., Kandaswamy, K. K., Suganthan, P. N., Sowdhamini, R., Martinetz, T. & Kolatkar, P. R., 31.03.2010, In: Journal of Biomolecular Structure and Dynamics. 28, 3, p. 405-414 10 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Protein Structure 100%
  • Support Vector Machine 100%
  • Protein 33%
  • Database 16%
  • Length 16%
  3 Citations (Scopus)

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

  Kandaswamy, K. K., Pugalenthi, G., Hartmann, E., Kalies, K. U., Möller, S., Suganthan, P. N. & Martinetz, T., 15.01.2010, In: Biochemical and Biophysical Research Communications. 391, 3, p. 1306-1311 6 p.

  Research output: Journal Articles › Journal articles › Research › peer-review

  • Protein 100%
  • Secretory Protein 100%
  • Signal Peptide 66%
  • Amino Terminal Sequence 60%
  • N-Terminus 50%
  16 Citations (Scopus)