Lemon-Tree preprint

We posted a preprint titled “Integrative multi-omics module network inference with Lemon-Tree” on the arXiv. The preprint describes the current status of our module networks inference software Lemon-Tree and demonstrates how it can be used to identify cancer driver genes from large-scale copy number variation and gene expression datasets such as generated by The Cancer Genome Atlas. All of this is joint work with Eric Bonnet.

Multi-species network inference preprint

We posted a preprint titled “Multi-species network inference improves gene regulatory network reconstruction for early embryonic development in Drosophila” on the arXiv. In this paper we use gene expression data measured during early embryonic development in six Drosophila species and networks of ChIP-chip and ChIP-seq interactions for developmental transcription factors in five species to demonstrate that the integration of data from comparable experiments in multiple species improves the inference of gene regulatory networks.

PLoS One paper

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!

Preprint L1-penalised regression

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.

Welcome Chris!

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!