We contributed to a paper by Ming-Mei Shang, Josefin Skogsberg and Johan Björkegren from the Cardiovascular Genomics group on “Lim domain binding 2 – a key driver of transendothelial migration of leukocytes and atherosclerosis” and published in Arteriosclerosis, Thrombosis, and Vascular Biology. Congrats to Ming-Mei who led the study!
We contributed to a paper by Maarten Houbraken and colleagues at IBCN titled “The Index-Based Subgraph Matching Algorithm with General Symmetries (ISMAGS): Exploiting symmetry for faster subgraph enumeration” and published in PLoS One. This paper introduces a novel subgraph matching algorithm which realises important speed-up compared to other methods by taking into account subgraph symmetries. Congrats to Sofie who did the work on our side and Maarten who led the study!
A preprint titled “Natural coordinate descent algorithm for L1-penalised regression in generalised linear models” is available on the arXiv. L1-penalised regression refers to the use of a penalty term that sums the absolute effect sizes of all parameters in a high-dimensional regression model to select the most important variables in the model. This paper uses a simple result from convex analysis to show that a solution mechanism (“soft-thresholding”) previously known for least-squares regression is in fact generic and also holds for regression with for instance binary or count-based data.
A warm welcome to Chris Banks who joins the lab as a postdoctoral research fellow. Chris completed a PhD in Informatics at the University of Edinburgh and will work on developing mathematical models and computational methods for reconstructing gene regulatory networks from diverse “omics” datasets. Welcome Chris!
Sofie finished her one year postdoc in the lab in good style by submitting a paper about her work on long-range genome interactions and will now join Jan Cools’ lab. Thanks for the hard work Sofie and all the best in your new position!
A preprint of our paper “Graph-based data integration predicts long-range regulatory interactions across the human genome” is available on arXiv and bioRxiv. In this paper we use graph-based methods to combine multiple datasets of open chromatin and gene expression information in matching cell types from the ENCODE project to predict long-range interactions between regulatory elements in the human genome and their target genes. Predicted interactions between can be browsed here.