A warm welcome to Ramin Hasibi who has joined the group as a PhD student. Ramin has a master degree in computer networks and a strong background in deep learning and machine learning more generally. Welcome!
Sid’s paper Application of long read sequencing to determine expressed antigen diversity in Trypanosoma brucei infections has been published in PLOS Neglected Tropical Diseases. Congrats again to Sid and everyone who contributed!
I’ll be at the EMBO symposium on regulatory epigenomics next week. Looking forward to it!
A warm welcome to Ammar Malik who has joined the group as a PhD student. Ammar has a degree in Computer Engineering and brings with him a lot of experience in machine learning. Welcome!
A postdoc position is available in my group, to develop machine learning methods for inferring causal gene networks from genome, epigenome and transcriptome sequencing data. For more information and application instructions, see here.
A new preprint, “High-dimensional Bayesian network inference from systems genetics data using genetic node ordering”, is available on bioRxiv. Bayesian networks are statistical models for gene regulatory networks, and their inference from large-scale omics data is a major problem in systems genetics. In this paper we present an algorithm to solve this problem that uses causal inference, topological sorting and variable selection, and that is much more efficient than traditional Markov chain Monte Carlo algorithms. The algorithm is implemented in the Findr and lassopv software packages.
We contributed two chapters to a Methods in Molecular Biology book on Gene Regulatory Networks: a chapter by Lingfei about the use of Findr for the inference of transcriptome-wide causal networks, and a chapter by Pau about the use of lemon-tree for the inference of differential module networks.
Four PhD positions in computer science are available at the Department of Informatics. These positions can be held in any of the department’s research areas (algorithms, bioinformatics, machine learning, optimization, programming theory, security, and visualization). Applicants with an interest in computational biology and machine learning are welcome to contact me prior to submitting their application.
For more details and application instructions, see here.
I will give a talk at the VIB training event
Challenges within and between omics data integration.