101 to 110 of 115 Results
Küster, Hansjörg, 2018, "Mittelalterliche Pflanzenreste von der Marktstätte und Brotlaube in Konstanz [Dataset]", https://doi.org/10.11588/data/ARWJHB, heiDATA, V1
During excavations in medieval Konstanz very many samples were taken for archaeobotanical analyses. Samples could be dated to different time layers from High to Late Middle Ages. Spelt, millet and oats were probably the most important cereals. But also flax, hemp, figs and spices... |
Jun 8, 2018 - Diagnostic and Interventional Radiology
Triphan, Simon; Biederer, Jürgen; Burmester, Kerstin; Fellhauer, Iven; Vogelmeier, Claus; Jörres, Rudolf; Kauczor, Hans-Ulrich; Heußel, Claus; Wielpütz, Mark; Jobst, Bertram, 2018, "Raw data and analysis scripts for "Design and application of an MR reference phantom for multicentre lung imaging trials"", https://doi.org/10.11588/data/FHOCRZ, heiDATA, V1
This dataset contains all MRI phantom data discussed in the related publication as well as the python scripts used to analyse them. The format is DICOM files, where institution names and adresses have been anonymized. Abstract Introduction: As there is an increasing number of mul... |
Cleo-Aron Weis, 2018, "Histopathology of thymectomy specimens from the MGTX-trial", https://doi.org/10.11588/data/NWE2JJ, heiDATA, V1, UNF:6:Od2UlnHG3ctanb4ikzIx4g== [fileUNF]
Background: The thymectomy specimens from the “thymectomy trial in non-thymomatous myasthenia gravis patients receiving prednisone therapy” (MGTX) [1] underwent rigid and comprehensive work-up, which results in a unique, spatially mapped dataset. Fig. 1 Specimen work-up: Work-up... |
Mar 5, 2018 - KnopLab
Kats, Ilia; Khmelinskii, Anton; Kschonsak, Marc; Huber, Florian; Knieß, Robert A.; Bartosik, Anna; Knop, Michael, 2018, "Mapping degradation signals and pathways in a eukaryotic N-terminome [data set]", https://doi.org/10.11588/data/9ZQIKF, heiDATA, V1
Data accompanying the paper "Mapping degradation signals and pathways in a eukaryotic N-terminome". |
Dec 4, 2017 - Experimental Biophysics
Hildenbrand, Georg; Metzler, Philipp; Pilarczyk, Goetz; Bobu, Vladimir; Hosser, Hiltraud; Fleckenstein, Jens; Krufczik, Matthias; Bestvater, Felix; Wenz, Frederik; Hausmann, Michael, 2017, "Dose Enhancement Effects of Gold Nanoparticles Specifically Targeting RNA in Breast Cancer Cells [Dataset]", https://doi.org/10.11588/data/N8NHE2, heiDATA, V1
Localization microscopy has shown to be capable of systematic investigations on the arrangement and counting of cellular uptake of gold nanoparticles (GNP) with nanometer resolution. In this article, we show that the application of specially modified RNA targeting gold nanopartic... |
Lochead, Julia; Schessner, Julia; Werner, Tobias; Wölfl, Stefan, 2017, "Bioinformatic Tool for the Analysis of Time-Resolved data: the TReCCA Analyser", https://doi.org/10.11588/data/UYHOBR, heiDATA, V1
The TReCCA Analyser is conceived to facilitate, speed up and intensify the analysis and representation of your time-resolved data, more specically in the case of cell culture assays. Without having to type any formula, it will perform at wish the following calculations: Control c... |
Jul 6, 2017 - Department of Pharmaceutical Biology
Holenya, Pavlo; Heigwer, Florian; Wölfl, Stefan, 2017, "Bioinformatic Tools for the Prediction of Key Regulatory Molecules in Signaltransduction Networks", https://doi.org/10.11588/data/10056, heiDATA, V1
Kinetic Operating Microarray Analyzer (KOMA) enables calibration and high-throughput analysis of quantitative microarray data collected by using kinetic detection protocol. This tool can be also helpful for analyzing data from any other analytical assays employing enzymatic signa... |
Camacho, Salvador; Schwieren, Christiane; Ruppel, Andreas, 2017, "Promoting water consumption using behavioral economics insights [Dataset]", https://doi.org/10.11588/data/10099, heiDATA, V1
Mexico has one of the largest overweight and obesity epidemics in the world and as a response, several actions aiming to reduce the obesity epidemic have been already set in place. Some of these actions include a specific action program for schools looking to turn the scholar env... |
Oct 28, 2016 - Multiple Myeloma Research Laboratory
Rème, Thierry; Emde, Martina; Seckinger, Anja; Hose, Dirk, 2016, "HDAMM-predictor: prediction of progression in asymptomatic myeloma patients", https://doi.org/10.11588/data/10092, heiDATA, V1
The HDAMM-predictor is based on microarray gene expression and predicts the risk of progression from asymptomatic to symptomatic myeloma. It divides the patients in three groups, from low to high risk to progress. It was generated according to the method published by Rème et al.... |
Huber, Florian; Bunina, Daria; Gupta, Ishaan; Khmelinski, Anton; Meurer, Matthias; Theer, Patrick; Steinmetz, Lars M.; Knop, Michael, 2016, "Protein abundance control by non-coding antisense transcription [Dataset]", https://doi.org/10.11588/data/10073, heiDATA, V4
Data accompanying the paper "Protein abundance control by non-coding antisense transcription" by Huber et al, 2016, Cell Reports. This contains FACS data for the noise analysis in the publication as well as single cell data from microscopy. |
