Towards Learning Self-Organized Criticality of Rydberg Atoms using Graph Neural Networks

Self-Organized Criticality (SOC) is a ubiquitous dynamical phenomenon believed to be responsible for the emergence of universal scale-invariant behavior in many, seemingly unrelated systems, such as forest fires, virus spreading or atomic excitation dynamics. SOC describes the buildup of large-scale and long-range spatio-temporal correlations as a result of only local interactions and dissipation. The simulation of SOC dynamics is typically based on Monte-Carlo (MC) methods, which are however numerically expensive and do not scale beyond certain system sizes. We investigate the use of Graph Neural Networks (GNNs) as an effective surrogate model to learn the dynamics operator for a paradigmatic SOC system, inspired by an experimentally accessible physics example: driven Rydberg atoms. To this end, we generalize existing GNN simulation approaches to predict dynamics for the internal state of the node. We show that we can accurately reproduce the MC dynamics as well as generalize along the two important axes of particle number and particle density. This paves the way to model much larger systems beyond the limits of traditional MC methods. While the exact system is inspired by the dynamics of Rydberg atoms, the approach is quite general and can readily be applied to other systems

Vermont Price Variation Analysis

Presentation to Vermont\u27s Green Mountain Care Board about a Price Variation Analysis undertaken in partnership with the University of Vermont College of Medicine and Wakely Consulting Group. The presentation outlined price variations across the state and suggested a process and methodology that the Board could use to set standard rates

JACUSA: site-specific identification of RNA editing events from replicate sequencing data

Background: RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by the members of the Adenosine deaminases that act on RNA (ADAR) family. Typically, editing sites are identified as RNA-DNA-differences (RDDs) in a comparison of genome and transcriptome data from next-generation sequencing experiments. However, a method for robust detection of site-specific editing events from replicate RNA-seq data has not been published so far. Even more surprising, condition-specific editing events, which would show up as differences in RNA-RNA comparisons (RRDs) and depend on particular cellular states, are rarely discussed in the literature. Results: We present JACUSA, a versatile one-stop solution to detect single nucleotide variant positions from comparing RNA-DNA and/or RNA-RNA sequencing samples. The performance of JACUSA has been carefully evaluated and compared to other variant callers in an in silico benchmark. JACUSA outperforms other algorithms in terms of the F measure, which combines precision and recall, in all benchmark scenarios. This performance margin is highest for the RNA-RNA comparison scenario. We further validated JACUSA’s performance by testing its ability to detect A→I events using sequencing data from a human cell culture experiment and publicly available RNA-seq data from Drosophila melanogaster heads. To this end, we performed whole genome and RNA sequencing of HEK-293 cells on samples with lowered activity of candidate RNA editing enzymes. JACUSA has a higher recall and comparable precision for detecting true editing sites in RDD comparisons of HEK-293 data. Intriguingly, JACUSA captures most A→I events from RRD comparisons of RNA sequencing data derived from Drosophila and HEK-293 data sets. Conclusion: Our software JACUSA detects single nucleotide variants by comparing data from next-generation sequencing experiments (RNA-DNA or RNA-RNA). In practice, JACUSA shows higher recall and comparable precision in detecting A→I sites from RNA-DNA comparisons, while showing higher precision and recall in RNA-RNA comparisons

Performance assessment of promoter predictions on ENCODE regions in the EGASP experiment

BACKGROUND: This study analyzes the predictions of a number of promoter predictors on the ENCODE regions of the human genome as part of the ENCODE Genome Annotation Assessment Project (EGASP). The systems analyzed operate on various principles and we assessed the effectiveness of different conceptual strategies used to correlate produced promoter predictions with the manually annotated 5' gene ends. RESULTS: The predictions were assessed relative to the manual HAVANA annotation of the 5' gene ends. These 5' gene ends were used as the estimated reference transcription start sites. With the maximum allowed distance for predictions of 1,000 nucleotides from the reference transcription start sites, the sensitivity of predictors was in the range 32% to 56%, while the positive predictive value was in the range 79% to 93%. The average distance mismatch of predictions from the reference transcription start sites was in the range 259 to 305 nucleotides. At the same time, using transcription start site estimates from DBTSS and H-Invitational databases as promoter predictions, we obtained a sensitivity of 58%, a positive predictive value of 92%, and an average distance from the annotated transcription start sites of 117 nucleotides. In this experiment, the best performing promoter predictors were those that combined promoter prediction with gene prediction. The main reason for this is the reduced promoter search space that resulted in smaller numbers of false positive predictions. CONCLUSION: The main finding, now supported by comprehensive data, is that the accuracy of human promoter predictors for high-throughput annotation purposes can be significantly improved if promoter prediction is combined with gene prediction. Based on the lessons learned in this experiment, we propose a framework for the preparation of the next similar promoter prediction assessment

Hard x-ray characterization of a HEFT single-reflection prototype

We have measured the hard X-ray reflectivity and imaging performance from depth graded W/Si multilayer coated mirror segments mounted in a single reflection cylindrical prototype for the hard X-ray telescopes to be flown on the High Energy Focusing Telescope (HEFT) balloon mission. Data have been obtained in the energy range from 18 - 170 keV at the European Synchrotron Radiation Facility and at the Danish Space Research Institute at 8 keV. The modeling of the reflectivity data demonstrate that the multilayer structure can be well described by the intended power law distribution of the bilayer thicknesses optimized for the telescope performance and we find that all the data is consistent with an interfacial width of 4.5 Å. We have also demonstrated that the required 5% uniformity of the coatings is obtained over the mirror surface and we have shown that it is feasible to use similar W/Si coatings for much higher energies than the nominal energy range of HEFT leading the way for designing Gamma-ray telescopes for future astronomical applications. Finally we have demonstrate 35 arcsecond Half Power Diameter imaging performance of the one bounce prototype throughout the energy range of the HEFT telescopes

Molecular dissection of Penelope transposable element regulatory machinery

© 2008 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Nucleic Acids Research 36 (2008): 2522-2529, doi:10.1093/nar/gkm1166Penelope-like elements (PLEs) represent a new class of retroelements identified in more than 80 species belonging to at least 10 animal phyla. Penelope isolated from Drosophila virilis is the only known transpositionally active representative of this class. Although the size and structure of the Penelope major transcript has been previously described in both D. virilis and D. melanogaster transgenic strains, the architecture of the Penelope regulatory region remains unknown. In order to determine the localization of presumptive Penelope promoter and enhancer-like elements, segments of the putative Penelope regulatory region were linked to a CAT reporter gene and introduced into D. melanogaster by P-element-mediated transformation. The results obtained using ELISA to measure CAT expression levels and RNA studies, including RT–PCR, suggest that the active Penelope transposon contains an internal promoter similar to the TATA-less promoters of LINEs. The results also suggest that some of the Penelope regulatory sequences control the preferential expression in the ovaries of the adult flies by enhancing expression in the ovary and reducing expression in the carcass. The possible significance of the intron within Penelope for the function and evolution of PLEs, and the effect of Penelope insertions on adjacent genes, are discussed.This work was supported by grants from Russian Academy of Sciences (Cell and Molecular Biology to M.E.), and Welcome Trust Grant (075698) to M.E and D.J.F

Hard x-ray characterization of a HEFT single-reflection prototype

We have measured the hard X-ray reflectivity and imaging performance from depth graded W/Si multilayer coated mirror segments mounted in a single reflection cylindrical prototype for the hard X-ray telescopes to be flown on the High Energy Focusing Telescope (HEFT) balloon mission. Data have been obtained in the energy range from 18 - 170 keV at the European Synchrotron Radiation Facility and at the Danish Space Research Institute at 8 keV. The modeling of the reflectivity data demonstrate that the multilayer structure can be well described by the intended power law distribution of the bilayer thicknesses optimized for the telescope performance and we find that all the data is consistent with an interfacial width of 4.5 Å. We have also demonstrated that the required 5% uniformity of the coatings is obtained over the mirror surface and we have shown that it is feasible to use similar W/Si coatings for much higher energies than the nominal energy range of HEFT leading the way for designing Gamma-ray telescopes for future astronomical applications. Finally we have demonstrate 35 arcsecond Half Power Diameter imaging performance of the one bounce prototype throughout the energy range of the HEFT telescopes

Assessing the Utility of Thermodynamic Features for microRNA Target Prediction under Relaxed Seed and No Conservation Requirements

BACKGROUND: Many computational microRNA target prediction tools are focused on several key features, including complementarity to 5'seed of miRNAs and evolutionary conservation. While these features allow for successful target identification, not all miRNA target sites are conserved and adhere to canonical seed complementarity. Several studies have propagated the use of energy features of mRNA:miRNA duplexes as an alternative feature. However, different independent evaluations reported conflicting results on the reliability of energy-based predictions. Here, we reassess the usefulness of energy features for mammalian target prediction, aiming to relax or eliminate the need for perfect seed matches and conservation requirement. METHODOLOGY/PRINCIPAL FINDINGS: We detect significant differences of energy features at experimentally supported human miRNA target sites and at genome-wide sites of AGO protein interaction. This trend is confirmed on datasets that assay the effect of miRNAs on mRNA and protein expression changes, and a simple linear regression model leads to significant correlation of predicted versus observed expression change. Compared to 6-mer seed matches as baseline, application of our energy-based model leads to ∼3-5-fold enrichment on highly down-regulated targets, and allows for prediction of strictly imperfect targets with enrichment above baseline. CONCLUSIONS/SIGNIFICANCE: In conclusion, our results indicate significant promise for energy-based miRNA target prediction that includes a broader range of targets without having to use conservation or impose stringent seed match rules

Computational analyses of eukaryotic promoters

Computational analysis of eukaryotic promoters is one of the most difficult problems in computational genomics and is essential for understanding gene expression profiles and reverse-engineering gene regulation network circuits. Here I give a basic introduction of the problem and recent update on both experimental and computational approaches. More details may be found in the extended references. This review is based on a summer lecture given at Max Planck Institute at Berlin in 2005