Progress in biology is increasingly driven by revolutions within molecular biology measuring cellular material at an unprecedented scale. Consequently, biology is changing into a computational science, analysing and interpreting gigantic volumes of complex data. The Leiden Computational Biology Center (LCBC) focusses on this new approach to biology with the aim to generate new biological insights with clinical applicabilities. It brings together computational biologists that are skilled in the newest technologies in data science and molecular technologies. As molecular technologies are pushing the field towards more precise data (across all tissues and towards single cells), more diverse data (multi-omics), at both spatial and temporal resolution, fundamentally new computational models are required that go way beyond tools that handle the data (bioinformatics), and can model all these aspects integrally. These developments define the strategic research themes on which the LCBC focusses, being models geared towards (1) single cell data, (2) integrative data, and (3) spatio-temporal data. LCBC fosters modeling approaches for promising new molecular data into approaches that push biology boundaries. To realize this aim we work on long-term research projects in close collaboration with biologist and clinicians, and capitalize by proposing medical applications based on insights generated from research done within the LCBC.
LCBC is a division of the Leiden University Medical Center.
We are excited to announce that our paper Visual Analysis of Mass Cytometry Data by Hierarchical Stochastic Neighbor Embedding Reveals Rare Cell Types, previously available on BiorXiv has been published in Nature Communications. The paper describes the application of HSNE, a hierarchical SNE-based technique that allows the exploration of datasets too large for other SNE-based techniques (such...
Our paper on Duchenne muscular dystrophy is published in Scientific Reports. The paper provides a comprehensive analysis of the expression patterns of dystrophin isoforms across human brain development uisng data from the Allen Brain Atlas, the Roadmap Epigenomics Consortium, and the FANTOM5 project. The results provide new insights into the cognitive phenotype associated with Duchenne muscular dystrophy.