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1 to 10 of 21 Results
Mar 5, 2018 - KnopLab
Ilia Kats; Anton Khmelinskii; Marc Kschonsak; Florian Huber; Robert A. Knieß; Anna Bartosik; Michael Knop, 2018, "Mapping degradation signals and pathways in a eukaryotic N-terminome [data set]", doi: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]", doi: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...
Sep 11, 2017 - Computer Assisted Clinical Medicine
Gaa, Tanja; Neumann, Wiebke ; Sudarski, Sonja; Attenberger, Ulrike I.; Schönberg, Stefan O.; Schad, Lothar R.; Zöllner, Frank G., 2017, "Comparison of perfusion models for quantitative T1 weighted DCE-MRI of rectal cancer [Dataset]", doi:10.11588/data/NULJJR, heiDATA, V1
Twenty-six patients with newly diagnosed rectal carcinoma underwent 3T MRI of the pelvis including a T1 weighted dynamic contrast enhanced (DCE) protocol before treatment. For eighteen patients, mean values for Plasma Flow (PF), Plasma Volume (PV) and Mean Transit Time (MTT) were...
Computer Assisted Clinical Medicine(Heidelberg University - Medical Faculty Mannheim)
Sep 11, 2017
Data publications from the Chair in Computer Assisted Clinical Medicine at the Medical Faculty Mannheim (Heidelberg University).
Jul 7, 2017 - Department of Pharmaceutical Biology
Lochead, Julia ; Schessner, Julia; Werner, Tobias ; Wölfl, Stefan, 2017, "Bioinformatic Tool for the Analysis of Time-Resolved data: the TReCCA Analyser", doi: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", doi: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...
Department of Pharmaceutical Biology(Heidelberg University - Institute of Pharmacy and Molecular Biotechnology)
Jul 6, 2017
Data publications and software from the Department of Pharmaceutical Biology at the Institute of Pharmacy and Molecular Biotechnology at Heidelberg University.
Mar 10, 2017 - AWI Experimental Economics
Camacho, Salvador; Schwieren, Christiane; Ruppel, Andreas, 2017, "Promoting water consumption using behavioral economics insights [Dataset]", doi: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...
Multiple Myeloma Research Laboratory(Heidelberg University)
Oct 28, 2016
This Dataverse contains research data from the Multiple Myeloma Research Laboratory.
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", doi: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....
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