13 Tereshchenkivska, office 110
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Dimitri Nowicki (Associate research professor at Institute of Cybernetics of NASU)
Abstract: We will present a review of fresh results in deep learning for bioinformatics.
First, we wil give a short introduction to bioinformatics, nature of its data and main problems.
Then we will briefly describe methods of mapping from Levenstein to Euclidean metrics, and unsupervised learning and clustering of bioinformatic data.
Next, we consider application of deep neural networks for protein function prediction as well as protein folding
Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction
Machine Learning: An Indispensable Tool in Bioinformatics
Deep Learning for mining big data in the natural sciences
Principal component analysis for clustering gene expression data
Reconstructing Protein Structures by Neural Network Pairwise Interaction Fields and Iterative Decoy Set Construction
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