TY - JOUR AU - Ferrè, F. AU - Colantoni, A. AU - Helmer-Citterich, M. PY - 2015 DA - 2015// TI - Revealing protein-lncRNA interaction JO - Brief Bioinform VL - 17 UR - https://doi.org/10.1093/bib/bbv031 DO - 10.1093/bib/bbv031 ID - Ferrè2015 ER - TY - JOUR AU - Bartel, D. P. PY - 2009 DA - 2009// TI - MicroRNAs: target recognition and regulatory functions JO - Cell VL - 136 UR - https://doi.org/10.1016/j.cell.2009.01.002 DO - 10.1016/j.cell.2009.01.002 ID - Bartel2009 ER - TY - JOUR AU - Ray, D. AU - Kazan, H. AU - Chan, E. T. AU - Peña Castillo, L. AU - Chaudhry, S. AU - Talukder, S. PY - 2009 DA - 2009// TI - Rapid and systematic analysis of the RNA recognition specificities of RNA-binding proteins JO - Nat Biotechnol VL - 27 UR - https://doi.org/10.1038/nbt.1550 DO - 10.1038/nbt.1550 ID - Ray2009 ER - TY - JOUR AU - Hafner, M. AU - Landthaler, M. AU - Burger, L. AU - Khorshid, M. AU - Hausser, J. AU - Berninger, P. PY - 2010 DA - 2010// TI - Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP JO - Cell VL - 141 UR - https://doi.org/10.1016/j.cell.2010.03.009 DO - 10.1016/j.cell.2010.03.009 ID - Hafner2010 ER - TY - JOUR AU - Stražr, M. AU - žitnik, M. AU - Zupan, B. AU - Ule, J. AU - Curk, T. PY - 2016 DA - 2016// TI - Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins JO - Bioinformatics VL - 32 UR - https://doi.org/10.1093/bioinformatics/btw003 DO - 10.1093/bioinformatics/btw003 ID - Stražr2016 ER - TY - JOUR AU - Maticzka, D. AU - Lange, S. J. AU - Costa, F. AU - Backofen, R. PY - 2014 DA - 2014// TI - GraphProt: modeling binding preferences of RNA-binding proteins JO - Genome Biol VL - 15 UR - https://doi.org/10.1186/gb-2014-15-1-r17 DO - 10.1186/gb-2014-15-1-r17 ID - Maticzka2014 ER - TY - JOUR AU - Yan, J. AU - Friedrich, S. AU - Kurgan, L. PY - 2016 DA - 2016// TI - A comprehensive comparative review of sequence-based predictors of DNA- and RNA-binding residues JO - Brief Bioinform VL - 17 UR - https://doi.org/10.1093/bib/bbv023 DO - 10.1093/bib/bbv023 ID - Yan2016 ER - TY - JOUR AU - Alipanahi, B. AU - Delong, A. AU - Weirauch, M. T. AU - Frey, B. J. PY - 2015 DA - 2015// TI - Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning JO - Nat Biotechnol VL - 33 UR - https://doi.org/10.1038/nbt.3300 DO - 10.1038/nbt.3300 ID - Alipanahi2015 ER - TY - JOUR AU - Pan, X. AU - Zhu, L. AU - Fan, Y. X. AU - Yan, J. PY - 2014 DA - 2014// TI - Predicting protein-RNA interaction amino acids using random forest based on submodularity subset selection JO - Comput Biol Chem VL - 53 UR - https://doi.org/10.1016/j.compbiolchem.2014.11.002 DO - 10.1016/j.compbiolchem.2014.11.002 ID - Pan2014 ER - TY - JOUR AU - Foat, B. C. AU - Morozov, A. V. AU - Bussemaker, H. J. PY - 2006 DA - 2006// TI - Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE JO - Bioinformatics VL - 22 UR - https://doi.org/10.1093/bioinformatics/btl223 DO - 10.1093/bioinformatics/btl223 ID - Foat2006 ER - TY - JOUR AU - Leibovich, L. AU - Paz, I. AU - Yakhini, Z. AU - Mandel-Gutfreund, Y. PY - 2013 DA - 2013// TI - DRIMust: a web server for discovering rank imbalanced motifs using suffix trees JO - Nucleic Acids Res VL - 41 UR - https://doi.org/10.1093/nar/gkt407 DO - 10.1093/nar/gkt407 ID - Leibovich2013 ER - TY - JOUR AU - Livi, C. M. AU - Blanzieri, E. PY - 2014 DA - 2014// TI - Protein-specific prediction of mRNA binding using RNA sequences, binding motifs and predicted secondary structures JO - BMC Bioinforma VL - 15 UR - https://doi.org/10.1186/1471-2105-15-123 DO - 10.1186/1471-2105-15-123 ID - Livi2014 ER - TY - JOUR AU - Ahmad, S. AU - Gromiha, M. M. AU - Sarai, A. PY - 2004 DA - 2004// TI - Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information JO - Bioinformatics VL - 20 UR - https://doi.org/10.1093/bioinformatics/btg432 DO - 10.1093/bioinformatics/btg432 ID - Ahmad2004 ER - TY - JOUR AU - Kloft, M. AU - Brefeld, U. AU - Sonnenburg, S. AU - Zien, A. PY - 2011 DA - 2011// TI - Lp-norm multiple kernel learning JO - J Mach Learn Res VL - 12 ID - Kloft2011 ER - TY - JOUR AU - Pan, X. AU - Xiong, K. PY - 2015 DA - 2015// TI - PredcircRNA: computational classification of circular RNA from other long non-coding RNA using hybrid features JO - Mol Biosyst VL - 11 UR - https://doi.org/10.1039/C5MB00214A DO - 10.1039/C5MB00214A ID - Pan2015 ER - TY - JOUR AU - LeCun, Y. AU - Bengio, Y. AU - Hinton, G. PY - 2015 DA - 2015// TI - Deep learning JO - Nature VL - 521 UR - https://doi.org/10.1038/nature14539 DO - 10.1038/nature14539 ID - LeCun2015 ER - TY - JOUR AU - Hinton, G. E. AU - Salakhutdinov, R. R. PY - 2006 DA - 2006// TI - Reducing the dimensionality of data with neural networks JO - Science VL - 313 UR - https://doi.org/10.1126/science.1127647 DO - 10.1126/science.1127647 ID - Hinton2006 ER - TY - JOUR AU - LeCun, Y. AU - Bottou, L. AU - Bengio, Y. AU - Haffner, P. PY - 1998 DA - 1998// TI - Gradient-based learning applied to document recognition JO - Proc IEEE VL - 86 UR - https://doi.org/10.1109/5.726791 DO - 10.1109/5.726791 ID - LeCun1998 ER - TY - JOUR AU - Zhou, J. AU - Troyanskaya, O. G. PY - 2015 DA - 2015// TI - Predicting effects of noncoding variants with deep learning-based sequence model JO - Nat Methods VL - 12 UR - https://doi.org/10.1038/nmeth.3547 DO - 10.1038/nmeth.3547 ID - Zhou2015 ER - TY - JOUR AU - Kelley, D. R. AU - Snoek, J. AU - Rinn, J. L. PY - 2016 DA - 2016// TI - Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks JO - Genome Res VL - 26 UR - https://doi.org/10.1101/gr.200535.115 DO - 10.1101/gr.200535.115 ID - Kelley2016 ER - TY - JOUR AU - LeCun, Y. PY - 1989 DA - 1989// TI - Backpropagation Applied to Handwritten Zip Code Recognition JO - Neural Comput VL - 1 UR - https://doi.org/10.1162/neco.1989.1.4.541 DO - 10.1162/neco.1989.1.4.541 ID - LeCun1989 ER - TY - STD TI - Zhang C, Yan J, Li C, Rui X, Liu L, Bie R. On Estimating Air Pollution from Photos Using Convolutional Neural Network. New York: ACM Multimedia (ACM-MM16): 2016. p. 297–301. ID - ref22 ER - TY - JOUR AU - Fischer, A. AU - Igel, C. PY - 2012 DA - 2012// TI - An Introduction to Restricted Boltzmann Machines JO - Lect Notes Comput Sci VL - 7441 UR - https://doi.org/10.1007/978-3-642-33275-3_2 DO - 10.1007/978-3-642-33275-3_2 ID - Fischer2012 ER - TY - JOUR AU - Zhang, S. AU - Zhou, J. AU - Hu, H. AU - Gong, H. AU - Chen, L. AU - Cheng, C. AU - Zeng, J. PY - 2015 DA - 2015// TI - A deep learning framework for modeling structural features of RNA-binding protein targets JO - Nucleic Acids Res VL - 44 UR - https://doi.org/10.1093/nar/gkv1025 DO - 10.1093/nar/gkv1025 ID - Zhang2015 ER - TY - JOUR AU - Quang, D. AU - Chen, Y. AU - Xie, X. PY - 2015 DA - 2015// TI - DANN: a deep learning approach for annotating the pathogenicity of genetic variants JO - Bioinformatics VL - 31 UR - https://doi.org/10.1093/bioinformatics/btu703 DO - 10.1093/bioinformatics/btu703 ID - Quang2015 ER - TY - JOUR AU - Pan, X. AU - Fan, Y. X. AU - Yan, J. AU - Shen, H. B. PY - 2016 DA - 2016// TI - IPMiner: Hidden ncRNA-protein interaction sequential pattern mining with stacked autoencoder for accurate computational prediction JO - BMC Genomics VL - 17 UR - https://doi.org/10.1186/s12864-016-2931-8 DO - 10.1186/s12864-016-2931-8 ID - Pan2016 ER - TY - JOUR AU - Srivastava, N. AU - Salakhutdinov, R. R. PY - 2914 DA - 2914// TI - Multimodal learning with deep boltzmann machines JO - J Mach Learn Res. VL - 15 ID - Srivastava2914 ER - TY - JOUR AU - Ngiam, J. AU - Khosla, A. AU - Kim, M. AU - Nam, J. AU - Lee, H. AU - Ng, A. Y. PY - 2011 DA - 2011// TI - Multimodal Deep Learning JO - IEEE Int Conf Mach Learn VL - 28 ID - Ngiam2011 ER - TY - JOUR AU - Kazan, H. AU - Ray, D. AU - Chan, E. T. AU - Hughes, T. R. AU - Morris, Q. PY - 2010 DA - 2010// TI - RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins JO - PLoS Comput Biol VL - 6 UR - https://doi.org/10.1371/journal.pcbi.1000832 DO - 10.1371/journal.pcbi.1000832 ID - Kazan2010 ER - TY - JOUR AU - Zhang, S. AU - Liu, C. C. AU - Li, W. AU - Shen, H. AU - Laird, P. W. AU - Zhou, X. J. PY - 2012 DA - 2012// TI - Discovery of multi-dimensional modules by integrative analysis of cancer genomic data JO - Nucleic Acids Res VL - 40 UR - https://doi.org/10.1093/nar/gks725 DO - 10.1093/nar/gks725 ID - Zhang2012 ER - TY - JOUR AU - Kim, H. AU - Park, H. PY - 2007 DA - 2007// TI - Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis JO - Bioinformatics VL - 23 UR - https://doi.org/10.1093/bioinformatics/btm134 DO - 10.1093/bioinformatics/btm134 ID - Kim2007 ER - TY - JOUR AU - Zdunek, R. AU - Cichocki, A. PY - 2006 DA - 2006// TI - Non-negative matrix factorization with quasi-newton optimization JO - Artif Intell Soft Comput VL - 87 ID - Zdunek2006 ER - TY - JOUR AU - Li, X. AU - Quon, G. AU - Lipshitz, H. D. AU - Morris, Q. PY - 2010 DA - 2010// TI - Predicting in vivo binding sites of RNA-binding proteins using mRNA secondary structure JO - RNA VL - 16 UR - https://doi.org/10.1261/rna.2017210 DO - 10.1261/rna.2017210 ID - Li2010 ER - TY - JOUR AU - Ray, D. AU - Kazan, H. AU - Cook, K. B. AU - Weirauch, M. T. AU - Najafabadi, H. S. AU - Li, X. PY - 2013 DA - 2013// TI - A compendium of RNA-binding motifs for decoding gene regulation JO - Nature VL - 499 UR - https://doi.org/10.1038/nature12311 DO - 10.1038/nature12311 ID - Ray2013 ER - TY - JOUR AU - Pan, X. Y. AU - Tian, Y. AU - Huang, Y. AU - Shen, H. B. PY - 2010 DA - 2010// TI - Towards better accuracy for missing value estimation of epistatic miniarray profiling data by a novel ensemble approach JO - Genomics VL - 97 UR - https://doi.org/10.1016/j.ygeno.2011.03.001 DO - 10.1016/j.ygeno.2011.03.001 ID - Pan2010 ER - TY - JOUR AU - Gupta, S. AU - Stamatoyannopoulos, J. A. AU - Bailey, T. L. AU - Noble, W. S. PY - 2007 DA - 2007// TI - Quantifying similarity between motifs JO - Genome Biol VL - 8 UR - https://doi.org/10.1186/gb-2007-8-2-r24 DO - 10.1186/gb-2007-8-2-r24 ID - Gupta2007 ER - TY - JOUR AU - Sephton, C. F. AU - Cenik, C. AU - Kucukural, A. AU - Dammer, E. B. AU - Cenik, B. AU - Han, Y. AU - Dewey, C. M. AU - Roth, F. P. AU - Herz, J. AU - Peng, J. AU - Moore, M. J. AU - Yu, G. PY - 2011 DA - 2011// TI - Identification of neuronal RNA targets of TDP-43-containing ribonucleoprotein complexes JO - J Biol Chem VL - 286 UR - https://doi.org/10.1074/jbc.M110.190884 DO - 10.1074/jbc.M110.190884 ID - Sephton2011 ER - TY - JOUR AU - Srivastava, N. AU - Hinton, G. E. AU - Krizhevsky, A. AU - Sutskever, I. AU - Salakhutdinov, R. PY - 2014 DA - 2014// TI - Dropout: a simple way to prevent neural networks from overfitting JO - J Mach Learn Res VL - 15 ID - Srivastava2014 ER - TY - STD TI - Ioffe S, Szegedy C. Batch normalization: Accelerating deep network training by reducing internal covariate shift. In: Proceedings of The 32nd International Conference on Machine Learning. vol. 32: 2015. p. 448–56. ID - ref39 ER - TY - JOUR AU - Lorenz, R. AU - Bernhart, S. H. AU - Hoener zu Siederdissen, C. AU - Tafer, H. AU - Flamm, C. AU - Stadler, P. F. AU - Hofacker, I. L. PY - 2011 DA - 2011// TI - ViennaRNA Package 2.0 JO - Algorithm Mol Biol VL - 6 UR - https://doi.org/10.1186/1748-7188-6-26 DO - 10.1186/1748-7188-6-26 ID - Lorenz2011 ER - TY - JOUR AU - Crooks, G. E. AU - Hon, G. AU - Chandonia, J. M. AU - Brenner, S. E. PY - 2004 DA - 2004// TI - WebLogo JO - A sequence logo generator, Genome Res VL - 14 ID - Crooks2004 ER - TY - CHAP AU - Nair, V. AU - Hinton, G. E. PY - 2010 DA - 2010// TI - Rectified linear units improve restricted boltzmann machines BT - Proceedings of the 27th International Conference on Machine Learning PB - Omnipress CY - Haifa ID - Nair2010 ER - TY - JOUR AU - Quang, D. AU - Xie, X. PY - 2016 DA - 2016// TI - DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences JO - Nucleic Acids Res VL - 44 UR - https://doi.org/10.1093/nar/gkw226 DO - 10.1093/nar/gkw226 ID - Quang2016 ER - TY - STD TI - Andrychowicz M, Denil M, Gomez S, Hoffman MW, Pfau D, et al. Learning to learn by gradient descent by gradient descent. 2016. arXiv:1606.04474 [cs.NE]. ID - ref44 ER - TY - JOUR AU - Yates, A. AU - Akanni, W. AU - Amode, M. R. AU - Barrell, D. AU - Billis, K. AU - Carvalho-Silva, D. PY - 2016 DA - 2016// TI - Ensembl 2016 JO - Nucleic Acids Res VL - 44 UR - https://doi.org/10.1093/nar/gkv1157 DO - 10.1093/nar/gkv1157 ID - Yates2016 ER - TY - JOUR AU - Svetlichnyy, D. AU - Imrichova, H. AU - Fiers, M. AU - Kalender Atak, Z. AU - Aerts, S. PY - 2015 DA - 2015// TI - Identification of High-Impact cis-Regulatory Mutations Using Transcription Factor Specific Random Forest Models JO - PLoS Comput Biol VL - 11 UR - https://doi.org/10.1371/journal.pcbi.1004590 DO - 10.1371/journal.pcbi.1004590 ID - Svetlichnyy2015 ER - TY - JOUR AU - Frith, M. C. AU - Li, M. C. AU - Weng, Z. PY - 2003 DA - 2003// TI - Cluster-Buster: finding dense clusters of motifs in DNA sequences JO - Nucleic Acids Res VL - 31 UR - https://doi.org/10.1093/nar/gkg540 DO - 10.1093/nar/gkg540 ID - Frith2003 ER - TY - STD TI - Smolensky P. Chapter 6: Information Processing in Dynamical Systems: Foundations of Harmony Theory. Cambridge: MIT Press; 1986, p. 194–281. ID - ref48 ER - TY - JOUR AU - Hinton, G. E. PY - 2010 DA - 2010// TI - A practical guide to training restricted Boltzmann machines JO - Momentum VL - 9 ID - Hinton2010 ER - TY - JOUR AU - Tieleman, T. PY - 2012 DA - 2012// TI - Lecture 6.5 - rmsprop: Divide the gradient by a run-ning average of its recent magnitude JO - COURSERA: Neural Netw Mach Learn VL - 4 ID - Tieleman2012 ER - TY - JOUR AU - Pedregosa, F. AU - Varoquaux, G. AU - Gramfort, A. AU - Michel, V. AU - Thirion, B. AU - Grisel, O. PY - 2011 DA - 2011// TI - Scikit-learn: Machine learning in Python JO - J Mach Learn Res VL - 12 ID - Pedregosa2011 ER -