Big data analytics in bioinformatics

This thesis presents new bioinformatic solutions that efficiently can analyze and investigate big data sets of various types. Three manuscripts are included in the thesis. The first manuscript shows how unsupervised learning techniques can extract the mechanistic patterns that underlie cellular development trajectories. In the second manuscript, a customized neural network is used to aid the development of treatments for diseases induced by aberrant RNA splicing. In the third manuscript, a computer simulation is used to discover certain molecular mechanisms that can help establish therapies for stroke-induced brain and tissue damages. Altogether, this thesis shows how “big data analytics in bioinformatics” can be approached in current research strategie