We have been featured in the German newspaper Tagesspiegel.
Here is the English translation of that article.
We have been featured in the German newspaper Tagesspiegel.
Here is the English translation of that article.
Our paper about CoDiNA, a method for comparing coexpression networks, has been accepted for publication by PLoS One. To our knowledge, it is the first method that allows for a comparison of transcriptome-wide networks and of as many networks as you wish. It can be applied to a diverse range of research questions, for instance to comparing coexpression networks, gene regulatory networks, abundance networks, and other types of networks. Networks can be compared between cell-types, tissues, species, or time-points, among others. Just let your imagination play. You will get as output information on which links are conserved across the networks you compare and which links have changed, either by being present in only a subset of networks or by having changed in their sign in some networks. Further, nodes are classified as conserved, specific or diverged between networks.
The development of CoDiNA was a big collaborative effort with most contributions from Eivind Almaas and Deisy Gysi. CoDiNA is implemented as an R package.
Yao-Chung is finally present in Berlin. Welcome Yao-Chung!
For a few months now, we have a couple of new group members:
Due to the COVID-19 situation, they haven’t physically joined us yet in Berlin. But we hope that they will soon be allowed to travel and start their projects here.
In the meantime, we are having online meetings and coffee breaks:
We have published an invited headline review in the Journal of the Royal Society Interface on the Construction, comparison and evolution of networks in life sciences and other disciplines. Our paper describes how biological networks change over time – in relatively short scales like during signal transduction and in relatively long scales like during development and evolution. We give a comprehensive overview about existing methods for analyzing such network changes. Moreover, we take a survey across non-biological sciences to explore how they investigate network changes. Our survey includes also some entertaining examples on the evolution of cooking recipes and the Marvel Universe.
We are offering a fully funded PhD position in our lab to work on the analysis of gene expression differences between brain of Alzheimer’s patients and controls. The focus will be on mono-allelically expressed genes to test the hypothesis that they are involved in establishing cellular diversity and selective vulnerability.
See the complete advertisement here: PhD_AlzheimerExpressionSignatures
We have acquired funding for a PhD position within a project that investigates a relationship between brain size and cognitive abilities in rodents from Chernobyl. We are interested in deciphering molecular signatures that determine differences in brain size and behavior.
See the complete advertisement here: PhD_BrainEvolution
We currently have an opening for a postdoc, with some flexibility about the actual research topic. The postdoc is expected to propose and develop a research project that fits to the general interests of the group. Requirements for the position are a Dr. rer. nat. or PhD in Biology or Bioinformatics or another relevant field. The ideal candidate would have a strong interest in human evolution and expertise within multiple of the following areas: conducting research with induced pluripotent stem cells, differentiation into neuronal cells, CRISPR/Cas9, functional investigation of transcription factors and non-coding RNAs, ChIP-Seq, ChIRP-Seq, RNA-Seq, gene regulatory networks, computational analysis of –omics data, R, Python, network analysis.
See the complete advertisement here: Postdoc_HumanEvolution.
Have a look at our commentary in Evolutionary Bioinformatics. We provide some background on our tool for testing selection of ncRNA genes, the SSS test. This tool should be useful for any new genome project or biomedical study to gain further insights into the evolution and potential functions of ncRNA genes.
Our paper in GBE describes human population differences in genes coding for gene regulatory factors. Surprisingly many of them seem to evolve under positive selection, among them long clusters of KRAB-ZNF genes. Some of the population differences might explain differences in prevalence in psychiatric disorders, such as schizophrenia.