My research focuses on genome and proteome evolution. Over the past few years, we have made progress to quantitatively understand how the genetic architecture of life was transformed during eukaryogenesis. We have brought to light how the distributions of protein coding gene and protein lengths evolved across the whole tree of life. Our findings show, quantitatively, that eukaryotes emerged as a second-order transition phase, arising from the tension of increasing gene length and the constraints on producing longer proteins on average. Evolutionary biologists have tried to unveil the mechanism leading to eukaryotes after the symbiosis between a Bacteria and an Archaea, referred as the "black hole at the heart of biology". We have demostrated that it occurred abruptly but yet continuously, at a critical point. The increase in cellular complexity induced by this evolutionary event unlocked the path towards subsequent biological transitions such as multicellularity, sexuality, sociability, and so on.
In recent years, research on pseudogene evolution, retrotransposons, 3D architecture of chromatin and transcription has been also carried out. Always a passionate of interdisciplinary teams.
Science is full of rules that simplify the way nature works. Simplifications that, many times, stand on our incomplete knowledge of the domain and can mislead posterior research. It is not always the most efficient way to learn but, for practical reasons, is a good strategy. This has been previously approached in the concept of Falsifiability by Karl Popper. Biology, in particular, is specially prone to this problem due to its intrinsic complexity.
The state of the art is the best we have. Nevertheless, exceptions can be relevant, causal of functionality and even have implications in human diseases.
Therefore, scientists supported by evidence and swimming against the tide, have big chances to make a difference if they are strong enough. In summary, there is no such unique way to develop science, but creativity, critical thinking and new perspectives lead straight to the conquest of new results, and if for any reason it is a must to ferret out where the mainstream is, trying alternative solutions that follow the parsimony principle will be my way to go.
Computational Biology, proteome and genome evolution, genomics.
Still interested on:
non-coding genes, pseudogenes, transcription, mobile DNA, systems biology, three-dimensional chromatin structure, stem cells, astrobiology, artificial intelligence, neural networks, models for the development of the central visual system.
"Fundamentals of programming in biomedice with Python". Enjoy it!
|
Bioinformática. Entre la carne y la máquina Enrique M. Muro |
Available @ El Pais |
|
Preparing a course on "Fundamentals of programming in biomedicine with Python". I will use a part of it to teach @ the Modul 4.2. Biostatistik und Bioinformatik. Working on the emergence of eukaryotes. My collaborators and me are quite excited, lets see what comes out of this. A Methodology to Study Pseudogenized lincRNAs. Talyan S, Andrade-Navarro MA, Muro EM. Methods Mol Biol. 2021;2324:49-63. doi: 10.1007/978-1-0716-1503-4_4. PMID: 34165708 DOI: 10.1007/978-1-0716-1503-4_4 PubMed
Some publications that represent my work
Complete list of publications: Included in Pubmed Not included in Pubmed TeachingI have been teaching at undergraduate/master/phD level since long ago. Here, at the Johannes Gutenberg University of Mainz, I devote part of my time to teach since 2014.
For I long time I realized that, due to the advance of technology in biology, it was necessary to fill-in an important gap in the CV of many graduated biologists. As soon as I had the opportunity, during the covid19-lockdown, I worked to cover that gap. The result of that effort is "Fundamentals of programming in biology with Python". Open positionsStudents interested in Master's or PhD thesis are welcome to contact me. |
