Computational Reconstruction of Missing Data in Biological Research

Discover the cutting-edge insights in Computational Reconstruction of Missing Data in Biological Research by Feng Bao. Published by Springer Verlag in 2021, this enlightening 105-page paperback offers a comprehensive exploration of various biological data scenarios where information may be missing. The author presents innovative machine learning models designed to enhance data analysis, including advanced techniques such as deep recurrent neural network recovery for feature missings, robust information theoretic learning for label missings, and structure-aware rebalancing for minor sample missings. This first edition is an essential read for researchers and professionals looking to deepen their understanding of data reconstruction in biological studies. Enhance your research capabilities with this invaluable resource!