Michael Golden will be presenting “Probabilistic Inference of Nucleotide Coevolution” at the Computational Statistics and Machine Learning seminar today at 15:30 in the Department of Statistics. His slides are available here.
Pairs of nucleotide positions within biologically functional nucleic acid secondary structures often exhibit evidence of coevolution that is consistent with base-pairing. PICNIC is a probabilistic sequence evolution model that assesses rates of mutation at base-paired sites in alignments of DNA or RNA sequences. PICNIC is able to fully account for an unknown secondary structure, and in doing so can be used to predict a secondary structure shared amongst an alignment of sequences. PICNIC was used to infer rates of coevolution associated with GC, AU (AT in DNA), and GU (GT in DNA) dinucleotides in non-coding RNA alignments, and single-stranded RNA and DNA virus alignments. Strong evidence was found for GU dinucleotides being selectively favoured at base-paired sites in non-coding RNA and RNA virus alignments, with marginal evidence for GT dinucleotides being selectively favoured at base-paired sites in DNA virus alignments. The strength of coevolution at base-paired sites in a SHAPE-MaP-determined HIV-1 NL4-3 RNA secondary structure and a corresponding alignment containing large numbers of HIV group 1M sequences was also measured, finding that the PICNIC-inferred degrees of coevolution were more strongly correlated with experimentally-determined SHAPE-MaP pairing scores than degrees of coevolution measured using three mutual information methods that do not take into account phylogenetic dependencies.
I will be giving a course with these lecture in TH18 at a advanced undergraduate course at the Department of Statistics
1 Enumeration in Phylogenetics
2. Tree Generating Processes
4. Statistical Alignment
5 Physics of Molecules: QM and MM
6 Integrators and Approximations
7 Applications I: Reactions
8 Applications II: Protein Folding
9 Small Molecules
10 Polya Enumeration
11 Graph Grammars and Reaction Prediction
12 3D Prediction from Graphs
13 Modeling the Evolution of Complex Objects: Languages, Patterns, Movements
14 The Comparative Method
15 Example I: Proteins
16 Example II: Networks
They will appear on this page as I finish them:
The present version can be found here:
The author – Istvan Miklos – believes he will always be ahead of the readers in writing. We would then write a review that would be published about the same time as the book was published and we put an extended report on this page:
We also give a summarizing lecture when we have finished the book. Earlier when we did this, we met every 2nd day doing about 20 pages each time, but it can depend on the individual book. We did a similar thing to Mike Steels 2016-book, which I believe was beneficial to both authors and readers.
The ideal number of participants in such a group is 3-5. It would have to be online since I will be Israel. I like to choose a time that is either starting or ending of working day so it interpheres minimally with work. If you know somebody interested in participating in this, please tell me. If it proves a crappy book, we will stop reading, but that is not what I expect.
What did we learn at: Origins of Life Conference – ISSOL17
- written by Jotun Hein
Overall attending the conference was a very useful since I haven’t been to an Origins Conference for more than 5 years and since I have stopped teaching Origins, in general, I don’t read so much on the chemical nitty-gritty.
The was much interesting material at the conference and of course, I met some people from Oxford, that I had never seen before working on catalysis.
The first day [Monday] was mainly devoted to Exoplanets and Meteorites/Comets/Transport of Organic Matter.
The second day [Tuesday] was the physical condition on earth 4 Billion or so years ago.
The third 1/2 day [Wednesday] was dedicated to the first chemical steps towards life.
The last 2 days were on the early evolution of life and more theoretical models.
Origins of Life studies are clearly getting a lot more attention/funding now. Computational studies play a much larger role. There are much more serious attempts at synthesizing life de Novo. But I can’t say there is a single convincing scenario for planet Earth. Exoplanets clearly are very exciting, but there is no way to study the architecture of life so far away [barring SETI – that was unrepresented at ISSOL] so all one can hope for a couple of centuries is observation of convincing bio-signatures.
There seemed to have been a lot of organizational problems. I didn’t know where to go and sleep and ended up sitting all night in the airport (while paying for a room at UCSD). Another person I met had experienced something else. The conference dinner was not very different from the free dinner and there were no arrangements of where to go. Anybody going to conferences/workshops knows that many connections are made at the evening socializing.
I, William Kurdahl and possibly some from the Oxford Catalysis will give an informal orientation about the meeting Tuesday, August 29th 3 PM in the small lecture room in The Department of Statistics, Oxford.
William and I both chose 5 papers/presentations that we liked.
These are the slides in progress:
Combinatorics of Recombination: https://www.dropbox.com/s/magvyy1jkkgin63/graduate%20lecture%201.6.17%20recombi.pptx?dl=0
Research Collaboration: https://www.dropbox.com/s/gveaj5rwp0f7eok/A%20Few%20Things.pptx?dl=0
Topics – both devoted to modelling in evolution: Models of Origins of Life & Phylogenetic
Time: Friday June 9th 2.00 PM – 4.30 PM
Venue: Department of Statistics, Oxford, Large Lecture Theatre
- 2.00 PM Generality and Robustness of the SVDQuartets Method for Phylogenetic Species Tree Estimation (Swofford)
Methods for inferring evolutionary trees based on phylogenetic invariants were first proposed nearly three decades ago, but have been virtually ignored by biologists. A new invariants-based method for estimating species trees under the multispecies coalescent model was recently developed by Julia Chifman and Laura Kubatko, building on earlier work by Elizabeth Allman, John Rhodes, and Nicholas Eriksson. This method comes from algebraic statistics and uses singular value decomposition to estimate the rank of matrices of site pattern frequencies. Although the approach shows great promise, its performance on empirical and simulated data sets has not been adequately evaluated.
I will give a general introduction to the SVDQuartets method and present some results from a simulation study currently in progress (collaboration with Laura Kubatko and Colby Long) that demonstrate that SVDQuartets is potentially highly robust to deviations from the standard evolutionary models assumed by other species-tree estimation methods.
- 3.30PM Autocatalytic Sets and the Origin of Life (Hordijk)
The main paradigm in origin of life research is that of an RNA world, where the idea is that life started with one or a few self-replicating RNA molecules. However, so far nobody has been able to show that RNA can catalyze its own template-directed replication. What has been shown experimentally, though, is that certain sets of RNA molecules can mutually catalyze each other’s formation from shorter RNA fragments. In other words, rather than having each RNA molecule replicate itself, they all help each other’s formation from basic building blocks, in a self-sustaining network of molecular cooperation.
Such a cooperative molecular network is an instance of an autocatalytic set, a concept that was formalized and studied mathematically and computationally as RAF theory.This theory has shown that autocatalytic sets are highly likely to exist in simple polymer models of chemical reaction networks, and that such sets can, in principle, be evolvable due to their hierarchical structure of many autocatalytic subsets. Furthermore, the framework has been applied succesfully to study real chemical and biological examples of autocatalytic sets.
In this talk I will give a general (and gentle) introduction to RAF theory, present its main results and how they could be relevant to the origin of life, and argue that the framework could possibly also be useful beyond chemistry, such as in analyzing ecosystems or even economic systems.
WINE IN COMMON AREA AFTER TALKS
Speaker: Stephen Altschul
Title: Dirichlet Mixtures, the Dirichlet Process, and the Topography of Amino Acid Multinomial Space
Venue: Tuesday May 23rd 3.30 PM Department of Statistics, Lecture Theatre (Lower Ground)
Abstract: The Dirichlet Process is used to estimate probability distributionsthat are mixtures of an unknown and unbounded number of components.Amino acid frequencies at homologous positions within related proteins have been fruitfully modeled by Dirichlet mixtures, and we have used the Dirichlet Process to construct such distributions. The resulting mixtures describe multiple alignment data substantially better than do those previously derived. They consist of over 500 components, in contrast to fewer than 40 previously, and provide a novel perspective on protein structure. Individual protein positions should be seen not as falling into one of several categories, but rather as arrayed near probability ridges winding through amino-acid multinomial space.
The slides will be made available after the talk.
Comment: Stephen Altschul has finally proven that I can’t add 2 and 2. I have attended Altschul Dinners at my College [University College, Oxford] and never thought of connecting the two words Altschul and Altschul despite their obvious similarity. It is in honour of Stephen’s grandmother, whose brother was Arthur Lehman Goodhart and Master of UNIV 1951–63.