@misc{7154, author = {Guseinov, Ruslan}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary data for "Programming temporal morphing of self-actuated shells"}}, doi = {10.15479/AT:ISTA:7154}, year = {2019}, } @misc{6060, author = {Vicoso, Beatriz}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary data for "Sex-biased gene expression and dosage compensation on the Artemia franciscana Z-chromosome" (Huylman, Toups et al., 2019). }}, doi = {10.15479/AT:ISTA:6060}, year = {2019}, } @misc{6074, abstract = {This dataset contains the supplementary data for the research paper "Haploinsufficiency of the intellectual disability gene SETD5 disturbs developmental gene expression and cognition". The contained files have the following content: 'Supplementary Figures.pdf' Additional figures (as referenced in the paper). 'Supplementary Table 1. Statistics.xlsx' Details on statistical tests performed in the paper. 'Supplementary Table 2. Differentially expressed gene analysis.xlsx' Results for the differential gene expression analysis for embryonic (E9.5; analysis with edgeR) and in vitro (ESCs, EBs, NPCs; analysis with DESeq2) samples. 'Supplementary Table 3. Gene Ontology (GO) term enrichment analysis.xlsx' Results for the GO term enrichment analysis for differentially expressed genes in embryonic (GO E9.5) and in vitro (GO ESC, GO EBs, GO NPCs) samples. Differentially expressed genes for in vitro samples were split into upregulated and downregulated genes (up/down) and the analysis was performed on each subset (e.g. GO ESC up / GO ESC down). 'Supplementary Table 4. Differentially expressed gene analysis for CFC samples.xlsx' Results for the differential gene expression analysis for samples from adult mice before (HC - Homecage) and 1h and 3h after contextual fear conditioning (1h and 3h, respectively). Each sheet shows the results for a different comparison. Sheets 1-3 show results for comparisons between timepoints for wild type (WT) samples only and sheets 4-6 for the same comparisons in mutant (Het) samples. Sheets 7-9 show results for comparisons between genotypes at each time point and sheet 10 contains the results for the analysis of differential expression trajectories between wild type and mutant. 'Supplementary Table 5. Cluster identification.xlsx' Results for k-means clustering of genes by expression. Sheet 1 shows clustering of just the genes with significantly different expression trajectories between genotypes. Sheet 2 shows clustering of all genes that are significantly differentially expressed in any of the comparisons (includes also genes with same trajectories). 'Supplementary Table 6. GO term cluster analysis.xlsx' Results for the GO term enrichment analysis and EWCE analysis for enrichment of cell type specific genes for each cluster identified by clustering genes with different expression trajectories (see Table S5, sheet 1). 'Supplementary Table 7. Setd5 mass spectrometry results.xlsx' Results showing proteins interacting with Setd5 as identified by mass spectrometry. Sheet 1 shows protein protein interaction data generated from these results (combined with data from the STRING database. Sheet 2 shows the results of the statistical analysis with limma. 'Supplementary Table 8. PolII ChIP-seq analysis.xlsx' Results for the Chip-Seq analysis for binding of RNA polymerase II (PolII). Sheet 1 shows results for differential binding of PolII at the transcription start site (TSS) between genotypes and sheets 2+3 show the corresponding GO enrichment analysis for these differentially bound genes. Sheet 4 shows RNAseq counts for genes with increased binding of PolII at the TSS.}, author = {Dotter, Christoph and Novarino, Gaia}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary data for the research paper "Haploinsufficiency of the intellectual disability gene SETD5 disturbs developmental gene expression and cognition"}}, doi = {10.15479/AT:ISTA:6074}, year = {2019}, } @misc{6062, abstract = {Open the files in Jupyter Notebook (reccomended https://www.anaconda.com/distribution/#download-section with Python 3.7).}, author = {Nardin, Michele}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary Code and Data for the paper "The Entorhinal Cognitive Map is Attracted to Goals"}}, doi = {10.15479/AT:ISTA:6062}, year = {2019}, } @misc{5573, abstract = {Graph matching problems for large displacement optical flow of RGB-D images.}, author = {Alhaija, Hassan and Sellent, Anita and Kondermann, Daniel and Rother, Carsten}, keywords = {graph matching, quadratic assignment problem<}, publisher = {Institute of Science and Technology Austria}, title = {{Graph matching problems for GraphFlow – 6D Large Displacement Scene Flow}}, doi = {10.15479/AT:ISTA:82}, year = {2018}, } @misc{5577, abstract = {Data on Austrian open access publication output at Emerald from 2013-2017 including data analysis.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{Emerald Austrian Publications 2013-2017}}, doi = {10.15479/AT:ISTA:89}, year = {2018}, } @misc{5578, abstract = {Data on Austrian open access publication output at IOP from 2012-2015 including data analysis.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{IOP Austrian Publications 2012-2015}}, doi = {10.15479/AT:ISTA:90}, year = {2018}, } @misc{5574, abstract = {Comparison of Scopus' and publisher's data on Austrian publication output at IOP. }, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{Data Check IOP Scopus vs. Publisher}}, doi = {10.15479/AT:ISTA:86}, year = {2018}, } @misc{5588, abstract = {Script to perform a simple exponential lifetime fit of a ROI on time stacks acquired with a FLIM X16 TCSPC detector (+example data)}, author = {Hauschild, Robert}, keywords = {FLIM, FRET, fluorescence lifetime imaging}, publisher = {Institute of Science and Technology Austria}, title = {{Fluorescence lifetime analysis of FLIM X16 TCSPC data}}, doi = {10.15479/AT:ISTA:0113}, year = {2018}, } @misc{5582, abstract = {Data on Austrian open access publication output at Taylor&Francis from 2013-2017 including data analysis.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{Taylor&Francis Austrian Publications 2013-2017}}, doi = {10.15479/AT:ISTA:94}, year = {2018}, } @misc{5581, abstract = {Data on Austrian open access publication output at Springer from 2013-2016 including data analysis.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{Springer Austrian Publications 2013-2016}}, doi = {10.15479/AT:ISTA:93}, year = {2018}, } @misc{5580, abstract = {Data on Austrian open access publication output at SAGE from 2013-2017 including data analysis.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{SAGE Austrian Publications 2013-2017}}, doi = {10.15479/AT:ISTA:92}, year = {2018}, } @misc{5579, abstract = {Data on Austrian open access publication output at RSC from 2013-2017 including data analysis.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{RSC Austrian Publications 2013-2017}}, doi = {10.15479/AT:ISTA:91}, year = {2018}, } @misc{5576, abstract = {Comparison of Scopus' and FWF's data on Austrian publication output at T&F.}, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{Data Check T&F Scopus vs. FWF}}, doi = {10.15479/AT:ISTA:88}, year = {2018}, } @misc{5575, abstract = {Comparison of Scopus' and FWF's data on Austrian publication output at RSC. }, author = {Villányi, Márton}, keywords = {Publication analysis, Bibliography, Open Access}, publisher = {Institute of Science and Technology Austria}, title = {{Data Check RSC Scopus vs. FWF}}, doi = {10.15479/AT:ISTA:87}, year = {2018}, } @misc{5584, abstract = {This package contains data for the publication "Nonlinear decoding of a complex movie from the mammalian retina" by Deny S. et al, PLOS Comput Biol (2018). The data consists of (i) 91 spike sorted, isolated rat retinal ganglion cells that pass stability and quality criteria, recorded on the multi-electrode array, in response to the presentation of the complex movie with many randomly moving dark discs. The responses are represented as 648000 x 91 binary matrix, where the first index indicates the timebin of duration 12.5 ms, and the second index the neural identity. The matrix entry is 0/1 if the neuron didn't/did spike in the particular time bin. (ii) README file and a graphical illustration of the structure of the experiment, specifying how the 648000 timebins are split into epochs where 1, 2, 4, or 10 discs were displayed, and which stimulus segments are exact repeats or unique ball trajectories. (iii) a 648000 x 400 matrix of luminance traces for each of the 20 x 20 positions ("sites") in the movie frame, with time that is locked to the recorded raster. The luminance traces are produced as described in the manuscript by filtering the raw disc movie with a small gaussian spatial kernel. }, author = {Deny, Stephane and Marre, Olivier and Botella-Soler, Vicente and Martius, Georg S and Tkacik, Gasper}, keywords = {retina, decoding, regression, neural networks, complex stimulus}, publisher = {Institute of Science and Technology Austria}, title = {{Nonlinear decoding of a complex movie from the mammalian retina}}, doi = {10.15479/AT:ISTA:98}, year = {2018}, } @misc{5586, abstract = {Input files and scripts from "Evolution of gene dosage on the Z-chromosome of schistosome parasites" by Picard M.A.L., et al (2018).}, author = {Vicoso, Beatriz}, keywords = {schistosoma, Z-chromosome, gene expression}, publisher = {Institute of Science and Technology Austria}, title = {{Input files and scripts from "Evolution of gene dosage on the Z-chromosome of schistosome parasites" by Picard M.A.L., et al (2018)}}, doi = {10.15479/AT:ISTA:109}, year = {2018}, } @misc{5583, abstract = {Data and scripts are provided in support of the manuscript "Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering", and the associated Python package FAPS, available from www.github.com/ellisztamas/faps. Simulation scripts cover: 1. Performance under different mating scenarios. 2. Comparison with Colony2. 3. Effect of changing the number of Monte Carlo draws The final script covers the analysis of half-sib arrays from wild-pollinated seed in an Antirrhinum majus hybrid zone.}, author = {Ellis, Thomas}, publisher = {Institute of Science and Technology Austria}, title = {{Data and Python scripts supporting Python package FAPS}}, doi = {10.15479/AT:ISTA:95}, year = {2018}, } @misc{5569, abstract = {Nela Nikolic, Tobias Bergmiller, Alexandra Vandervelde, Tanino G. Albanese, Lendert Gelens, and Isabella Moll (2018) “Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations” Nucleic Acids Research, doi: 10.15479/AT:ISTA:74; microscopy experiments by Tobias Bergmiller; image and data analysis by Nela Nikolic.}, author = {Bergmiller, Tobias and Nikolic, Nela}, keywords = {microscopy, microfluidics}, publisher = {Institute of Science and Technology Austria}, title = {{Time-lapse microscopy data}}, doi = {10.15479/AT:ISTA:74}, year = {2018}, } @misc{5587, abstract = {Supporting material to the article STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH boundscoli.dat Flux Bounds of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium. polcoli.dat Matrix enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium, obtained from the soichiometric matrix by standard linear algebra (reduced row echelon form). ellis.dat Approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium obtained with the Lovasz method. point0.dat Center of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium obtained with the Lovasz method. lovasz.cpp This c++ code file receives in input the polytope of the feasible steady states of a metabolic network, (matrix and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding the polytope with the Lovasz method NB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. For further details we refer to PLoS ONE 10.4 e0122670 (2015). sampleHRnew.cpp This c++ code file receives in input the polytope of the feasible steady states of a metabolic network, (matrix and bounds), the ellipsoid rounding the polytope, a point inside and it gives in output a max entropy sampling at fixed average growth rate of the steady states by performing an Hit-and-Run Monte Carlo Markov chain. NB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. For further details we refer to PLoS ONE 10.4 e0122670 (2015).}, author = {De Martino, Daniele and Tkacik, Gasper}, keywords = {metabolic networks, e.coli core, maximum entropy, monte carlo markov chain sampling, ellipsoidal rounding}, publisher = {Institute of Science and Technology Austria}, title = {{Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH"}}, doi = {10.15479/AT:ISTA:62}, year = {2018}, }