Prediction of gene–phenotype associations in humans, mice, and plants using phenologs

All authors are with the Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712, USA. -- Ulf Martin Singh-Blom is with the Program in Computational and Applied Mathematics, The University of Texas at Austin, Austin, TX 78712, USA, and th Unit of Computational Medicine, Department of Medicine, Karolinska Institutet, Stockholm 171 76, Sweden. -- Kriston L. McGary is with the Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.Background: Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such “orthologous phenotypes,” or “phenologs,” are examples of deep homology, and may be used to predict additional candidate disease genes. Results: In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data — from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans — establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene–phenotype associations, as for the Arabidopsis response to vernalization phenotype. Conclusions: We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species.Center for Systems and Synthetic BiologyInstitute for Cellular and Molecular [email protected]

MOTIFATOR: detection and characterization of regulatory motifs using prokaryote transcriptome data

Summary: Unraveling regulatory mechanisms (e.g. identification of motifs in cis-regulatory regions) remains a major challenge in the analysis of transcriptome experiments. Existing applications identify putative motifs from gene lists obtained at rather arbitrary cutoff and require additional manual processing steps. Our standalone application MOTIFATOR identifies the most optimal parameters for motif discovery and creates an interactive visualization of the results. Discovered putative motifs are functionally characterized, thereby providing valuable insight in the biological processes that could be controlled by the motif.

Supporting Initial Teacher Education Students Assessment Literacy and Capability Development

Recent curricular reform in Ireland has utilised classroom-based assessments as part of the national assessment strategy at the junior level in post-primary education. This calls for teachers to exercise their judgement in relation to their pupils' capability which is recorded for the certified national award of the Junior Cycle Profile of Achievement (JCPA). Ensuring effective assessment in this regard requires the development of assessment literacy and capability in the teaching cohort which starts on the continuum of teacher development at the initial teacher education (ITE) phase. Teacher judgement in assessment is reliant on multiple factors that impact on the assessment outcome. It is therefore important to design components of ITE programmes that provide opportunity to strategically develop this capability for implementation in practice. The case study presented in this paper presents an initial analysis of the practices and experiences of (n=87) Initial Teacher Education (ITE) students as they engage in a peer assessment activity that is part of an assessment literacy and capability development strategy on a technology education ITE programme. This was facilitated through the use of Adaptive Comparative Judgement sessions (ACJ). In these sessions, the participants engaged in the establishment of assessment criteria and implemented them in the holistic assessment of peers' work through the ACJ method along with providing formative feedback and making a summative judgement of the quality of the work. The findings present the usefulness of ACJ in providing pre-service teachers a space to develop assessment literacy and capability through the active and experiential learning approach taken

COMPTEL observations of the quasar PKS 0528+134 during the first 3.5 years of the CGRO mission

The COMPTEL observations of the blazar-type quasar PKS 0528+134 in the energy range 0.75 MeV to 30 MeV carried out between April 1991 and September 1994 have been analyzed. During the first two years PKS 0528+134 was most significantly detected at energies above 3 MeV. During the last year there is only evidence for the quasar at energies below 3 MeV indicating a spectral change. The time-averaged COMPTEL energy spectrum between 0.75 MeV and 30 MeV is well represented by a power-law shape. Spectra collected from different observational periods reveal different power-law shapes: a hard state during flaring observations reported by EGRET, and a soft state otherwise. The combined simultaneous EGRET and COMPTEL spectra indicate these two spectral states as well. During low intensisty gamma-ray phases no spectral break is obvious from the combined COMPTEL and EGRET measurements. For the gamma-ray flaring phases however, the combined COMPTEL and EGRET data require a spectral bending at MeV-energies. By fitting broken power-law functions the best-fit values for the break in photon index range between 0.6 and 1.7, and for the break energy between ~5 MeV and ~20 MeV. Because the flux values measured by COMPTEL below 3 MeV in both states are roughly equal, the observations would be consistent with an additional spectral component showing up during gamma-ray flaring phases of PKS 0528+134. Such a component could be introduced by e.g. a high-energy electron-positron population with a low-energy cutoff in their bulk Lorentz factor distribution. The multiwavelength spectrum of PKS 0528+134 for gamma-ray flaring phases shows that the major energy release across the entire electro-magnetic spectrum is measured at MeV-energies.Comment: 10 pages, 8 postscript figures, latex, to appear in: A&A 328, 33 (1997

COMPTEL Observations of AGN at MeV-Energies

The COMPTEL experiment aboard CGRO, exploring the previously unknown sky at MeV-energies, has so far detected 10 Active Galactic Nuclei (AGN): 9 blazars and the radio galaxy Centaurus A. No Seyfert galaxy has been found yet. With these results COMPTEL has opened the field of extragalactic Gamma-ray astronomy in the MeV-band.Comment: 4 pages, 2 figures including 1 color plot, to appear in the Proceedings of the 3rd INTEGRAL Workshop "The Extreme Universe", held in Taormina, Italy, 14-18 September 199

Tail asymptotics of a Markov-modulated infinite-server queue

This paper analyzes large deviation probabilities related to the number of customers in a Markov modulated infinite-server queue, with state-dependent arrival and service rates. Two specific scalings are studied: in the first, just the arrival rates are linearly scaled by $N$ (for large $N$), whereas in the second in addition the Markovian background process is sped up by a factor $N^{1+\epsilon}$, for some $\epsilon>0$. In both regimes, (transient and stationary) tail probabilities decay essentially exponentially, where the associated decay rate corresponds to that of the probability that the sample mean of i.i.d.\ Poisson random variables attains an atypical value

Super-resolution provided by the arbitrarily strong superlinearity of the blackbody radiation

Blackbody radiation is a fundamental phenomenon in nature, and its explanation by Planck marks a cornerstone in the history of Physics. In this theoretical work, we show that the spectral radiance given by Planck's law is strongly superlinear with temperature, with an arbitrarily large local exponent for decreasing wavelengths. From that scaling analysis, we propose a new concept of super-resolved detection and imaging: if a focused beam of energy is scanned over an object that absorbs and linearly converts that energy into heat, a highly nonlinear thermal radiation response is generated, and its point spread function can be made arbitrarily smaller than the excitation beam focus. Based on a few practical scenarios, we propose to extend the notion of super-resolution beyond its current niche in microscopy to various kinds of excitation beams, a wide range of spatial scales, and a broader diversity of target objects

Maximal Sharing in the Lambda Calculus with letrec

Increasing sharing in programs is desirable to compactify the code, and to avoid duplication of reduction work at run-time, thereby speeding up execution. We show how a maximal degree of sharing can be obtained for programs expressed as terms in the lambda calculus with letrec. We introduce a notion of `maximal compactness' for lambda-letrec-terms among all terms with the same infinite unfolding. Instead of defined purely syntactically, this notion is based on a graph semantics. lambda-letrec-terms are interpreted as first-order term graphs so that unfolding equivalence between terms is preserved and reflected through bisimilarity of the term graph interpretations. Compactness of the term graphs can then be compared via functional bisimulation. We describe practical and efficient methods for the following two problems: transforming a lambda-letrec-term into a maximally compact form; and deciding whether two lambda-letrec-terms are unfolding-equivalent. The transformation of a lambda-letrec-term $L$ into maximally compact form $L_0$ proceeds in three steps: (i) translate L into its term graph $G = [[ L ]]$; (ii) compute the maximally shared form of $G$ as its bisimulation collapse $G_0$; (iii) read back a lambda-letrec-term $L_0$ from the term graph $G_0$ with the property $[[ L_0 ]] = G_0$. This guarantees that $L_0$ and $L$ have the same unfolding, and that $L_0$ exhibits maximal sharing. The procedure for deciding whether two given lambda-letrec-terms $L_1$ and $L_2$ are unfolding-equivalent computes their term graph interpretations $[[ L_1 ]]$ and $[[ L_2 ]]$, and checks whether these term graphs are bisimilar. For illustration, we also provide a readily usable implementation.Comment: 18 pages, plus 19 pages appendi

Teamwork Satisfaction And Student Attitudes Towards Online Learning During An Engineering Problem And Project Based Learning (PBL) Module

Research has shown that students that report high levels of learner satisfaction and positive attitudes are more likely to succeed within the online environment. This is reflected in the considerable body of research that focuses on these factors across a range of academic disciplines. By assessing students\u27 attitudes and satisfaction, educators gain a valuable affective perspective that allows for a more complete examination of strategy effectiveness. This paper examines teamwork satisfaction and student attitude towards online learning, while also highlighting elements of successful online collaboration as identified by students using the instruments developed by Hasler-Waters & Napier, Ku et al, and Tseng et al. This case study was carried out over a seven-week period with first-year engineering students (N=94), in a module entitled Design for Manufacture, during the COVID-19 pandemic. The findings revealed high levels of student satisfaction and attitudes towards working in teams in the online environment while participating in problem and project-based learning (PBL). Additionally, the findings outline multiple factors that affect the success of online collaboration. The relevance of these findings is then discussed in the context of an increasing move towards blended and online engineering education provision