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Self-organizing neural networks to support the discovery of DNA-binding motifs.

, , , and . Neural Networks, 19 (6-7): 950-962 (2006)

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A New Approach to Gene Prediction Using the Self-Organizing Map., , , and . CSB, page 444-445. IEEE Computer Society, (2003)Self-Organizing Maps of Position Weight Matrices for Motif Discovery in Biological Sequences., , , and . Artif. Intell. Rev., 24 (3-4): 397-413 (2005)Discovering homotypic binding events at high spatial resolution., , , , , , and . Bioinformatics, 26 (24): 3028-3034 (2010)Transcription factor binding site identification using the self-organizing map., , , , and . Bioinformatics, 21 (9): 1807-1814 (2005)Deconvolving sequence features that discriminate between overlapping regulatory annotations., , , and . PLoS Computational Biology, (2017)Characterizing Protein-DNA Binding Event Subtypes in ChIP-Exo Data., , , , and . RECOMB, volume 10812 of Lecture Notes in Computer Science, page 291-292. Springer, (2018)Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models., , , and . BMC Bioinformatics, (2004)miniMDS: 3D structural inference from high-resolution Hi-C data., and . Bioinformatics, 33 (14): i261-i266 (2017)Self-organizing neural networks to support the discovery of DNA-binding motifs., , , and . Neural Networks, 19 (6-7): 950-962 (2006)An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding., , , , , , , and . RECOMB, volume 8394 of Lecture Notes in Computer Science, page 175-176. Springer, (2014)