Spatiotemporal convolutional network for time-series prediction and causal inference

Making predictions in a robust way is not easy for nonlinear systems. In this work, a neural network computing framework, i.e., a spatiotemporal convolutional network (STCN), was developed to efficiently and accurately render a multistep-ahead prediction of a time series by employing a spatial-temporal information (STI) transformation. The STCN combines the advantages of both the temporal convolutional network (TCN) and the STI equation, which maps the high-dimensional/spatial data to the future temporal values of a target variable, thus naturally providing the prediction of the target variable. From the observed variables, the STCN also infers the causal factors of the target variable in the sense of Granger causality, which are in turn selected as effective spatial information to improve the prediction robustness. The STCN was successfully applied to both benchmark systems and real-world datasets, all of which show superior and robust performance in multistep-ahead prediction, even when the data were perturbed by noise. From both theoretical and computational viewpoints, the STCN has great potential in practical applications in artificial intelligence (AI) or machine learning fields as a model-free method based only on the observed data, and also opens a new way to explore the observed high-dimensional data in a dynamical manner for machine learning.Comment: 23 pages, 6 figure

Quantifying the functional and evolutionary relationships among sequences, transcription factor binding and gene expression

A central challenge in regulatory genomics today is to understand the precise relationship between regulatory sequences, transcription factor (TF) binding and gene expression. Many studies have discussed how TFs recognize their DNA binding sites. However, it is not well understood how the various factors that influence TF-DNA binding alter the cascade of gene expression. Moreover, mutations in regulatory sequences are a key driving force of evolution and diseases. A number of studies have examined the sequence motif turnover and divergence in TF binding across species. However, there is currently a lack of clarity on what these changes mean to enhancer function. In this thesis, we used computational and statistical methods to quantitatively and systematically examine the relationships among regulatory sequences, TF binding, and gene expression, from both functional and evolutionary perspectives. At the functional level, we extended thermodynamics-based statistical models of the genetic sequence-to-function relationship to accurately predict gene expression. We incorporated chromatin accessibility and structural biological data into the models, described in Chapter 2 and 3. In doing so, we aimed to better identify transcription factor binding sites likely to influence gene expression, and thus, enhance the models’ capacity to predict gene expression. We demonstrated these improvements to gene expression modeling in Drosophila melanogaster by integrating DNaseI hypersensitivity assays and DNA shape. At the evolutionary level, we focused on regulatory variations between two distant Drosophila species to access inherent properties of enhancers, as described in Chapter 4. We used statistical and computational approaches to quantitatively examine the extent to which sequence and accessibility variations can predict TF occupancy divergence and enhancer activity change. We also found combinatorial TF binding can buffer variations at individual TF level to avoid drastic gene expression changes

Incorporating Chromatin Accessibility Data into Sequence-to-Expression Modeling

AbstractPrediction of gene expression levels from regulatory sequences is one of the major challenges of genomic biology today. A particularly promising approach to this problem is that taken by thermodynamics-based models that interpret an enhancer sequence in a given cellular context specified by transcription factor concentration levels and predict precise expression levels driven by that enhancer. Such models have so far not accounted for the effect of chromatin accessibility on interactions between transcription factor and DNA and consequently on gene-expression levels. Here, we extend a thermodynamics-based model of gene expression, called GEMSTAT (Gene Expression Modeling Based on Statistical Thermodynamics), to incorporate chromatin accessibility data and quantify its effect on accuracy of expression prediction. In the new model, called GEMSTAT-A, accessibility at a binding site is assumed to affect the transcription factor’s binding strength at the site, whereas all other aspects are identical to the GEMSTAT model. We show that this modification results in significantly better fits in a data set of over 30 enhancers regulating spatial expression patterns in the blastoderm-stage Drosophila embryo. It is important to note that the improved fits result not from an overall elevated accessibility in active enhancers but from the variation of accessibility levels within an enhancer. With whole-genome DNA accessibility measurements becoming increasingly popular, our work demonstrates how such data may be useful for sequence-to-expression models. It also calls for future advances in modeling accessibility levels from sequence and the transregulatory context, so as to predict accurately the effect of cis and trans perturbations on gene expression

Europium-doped calcium pyrophosphates : allotropic forms and photoluminescent properties

In a search for new luminescent biological probes, we synthesized calcium pyrophosphates doped with europium up to an atomic Eu/(Eu+Ca) ratio of 2%. They were prepared by coprecipitating a mixture of calcium and europium salts with phosphate. After heating at 900°C in air, two phases coexisted, identified as the β calcium pyrophosphate form and EuPO4. Heating near 1250°C in air, during the β→ transformation, europium ions substitute for calcium ions in the * calcium pyrophosphate structure as demonstrated by the spectroscopic study. Europium ions with both valence states (divalent and trivalent) were observed in the samples. Following the synthesis procedure, partial reduction of Eu3+ took place even in an oxidizing atmosphere. The 0.5%-doped compound could serve as a sensitive probe in biological applications. Depending on the excitation wavelength, the luminescence occurs either in the red or in the blue regions, which discriminates it from parasitic signals arising from other dyes or organelles in live cells

Integral and Rxte/Asm Observations on Igr J17098-3628

To probe further the possible nature of the unidentified source IGR J17098-3628, we have carried out a detailed analysis of its long-term time variability as monitored by RXTE/ASM, and of its hard X-ray properties as observed by INTEGRAL. INTEGRAL has monitored this sky region over years and significantly detected IGR J17098-3628 only when the source was in this dubbed active state. In particular, at $\ge$ 20 keV, IBIS/ISGRI caught an outburst in March 2005, lasting for $\sim$5 days with detection significance of 73$\sigma$ (20-40 keV) and with the emission at $<$200 keV. The ASM observations reveal that the soft X-ray lightcurve shows a similar outburst to that detected by INTEGRAL, however the peak of the soft X-ray lightcurve either lags, or is preceded by, the hard X-ray ($>$20 keV) outburst by $\sim$2 days. This resembles the behavior of X-ray novae like XN 1124-683, hence it further suggests a LMXB nature for IGR J17098-3628. While the quality of the ASM data prevents us from drawing any definite conclusions, these discoveries are important clues that, coupled with future observations, will help to resolve the as yet unknown nature of IGR J17098-3628.Comment: 15 pages, 7 figure, accepted in PAS

Galloway-Mowat syndrome: Prenatal ultrasound and perinatal magnetic resonance imaging findings

AbstractObjectiveTo present prenatal ultrasound and perinatal magnetic resonance imaging (MRI) findings of Galloway-Mowat syndrome.Case ReportA 31-year-old woman, gravida 3, para 2, was referred for genetic counseling at 29 weeks of gestation because of abnormal ultrasound findings and a previous child with Galloway-Mowat syndrome. During this pregnancy, microcephaly, intrauterine growth restriction (IUGR), and oligohydramnios were first noted at 27 weeks of gestation. Repeated ultrasounds showed microcephaly, IUGR, and oligohydramnios. MRI performed at 32 weeks of gestation showed reduced sulcation of the brain, pachygyria, poor myelination of the white matter, and cerebellar atrophy. A diagnosis of recurrent Galloway-Mowat syndrome was made. At 40 weeks of gestation, a 2,496-g female baby was delivered with microcephaly, a narrow slopping forehead, epicanthic folds, microphthalmos, a highly arched palate, a small midface, a beaked nose, thin lips, large low-set floppy ears, clenched hands, and arachnodactyly. Postnatal MRI findings were consistent with the prenatal diagnosis. Renal ultrasound showed enlarged bilateral kidneys with increased echogenicity. At the age of 2 weeks, the infant became edematous and developed nephrotic syndrome.ConclusionMicrocephaly, IUGR, and oligohydramnios are significant ultrasound triad of fetal Galloway-Mowat syndrome. Prenatal ultrasound diagnosis of microcephaly, IUGR, and oligohydramnios in late second trimester or in early third trimester should alert clinicians to the possibility of Galloway-Mowat syndrome and prompt a detailed search of abnormal sulcation, cortical gyral maldevelopment, and cerebellar atrophy by fetal ultrafast MRI