cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14056602
title: Putative Looping Factor ZNF143/ZFP143 is an Essential Transcriptional Regulator with No Looping Function

description: Overview

This repository contains all the raw fastSPT, FRAP, absolute abundance quantification data, and DESeq2 outputs associated with “Putative Looping Factor ZNF143/ZFP143 is an Essential Transcriptional Regulator with No Looping Function”. 

Cell lines, conditions, and experiments

This repository has data for the following experiments, cell lines, and conditions. 

fastSPT tracks and FRAP quantification for:



Histone H2B

Halo-NLS

CTCF C87

Clone D untreated

Clone D ∆ZFP143 (2-4h)

Clone A ZFP143 untreated

Clone A ZFP143 ∆CTCF (2-4h)

Clone B ZFP143 untreated

Clone B ZFP143 ∆CTCF (2-4h)


FRAP quantification for:



Clone A CTCF untreated

Clone A CTCF ∆ZFP143 (2-4h)

Clone B CTCF untreated

Clone B CTCF ∆ZFP143 (2-4h)

WT mESC pDNN13 transfection

WT mESC pDNN14 transfection

WT mESC pDNN15 transfection


DESeq2 outputs for:



Clone A/B ∆ZFP143 vs untreated PRO-seq

Clone A/B ∆CTCF vs untreated PRO-seq

Clone A/B ∆ZFP143/∆CTCF vs untreated PRO-seq

Clone D ∆ZFP143 vs untreated PRO-seq


Other files:



ZFP143 abundance quantification

The parameters used for tracking (tracking_config.toml)

The parameters used to get nuclear masks for fastSPT data (masking_params.csv)
DOI: 10.18419/darus-4447/1
title: supplementary.pdf

description: The supplemental material which contains mathematical derivations for the results presented in the main paper, a comparison to Monte Carlo sampling and additional use cases.
DOI: 10.18419/darus-4447
title: Supplementary Material for Uncertainty-aware Spectral Visualization

description: In this supplemental material, we provide supplemental information (PDF document with derivations of the results presented in the paper and two additional use cases) and the supplementary video for uncertainty-aware spectral analysis. We model an uncertain time series as a multivariate Gaussian process. We propagate the uncertainty and explicitly compute the probability distribution in the spectral domain. In the video, we use our interactive visual analysis tool to analyze these distributions. This material complements the paper on Uncertainty-aware Spectral Visualization.
DOI: 10.18419/darus-4447/2
title: video.mp4

description: A video that shows how the visual analysis approach can be used for uncertainty-aware spectral analaysis.
DOI: 10.18419/darus-4452/1
title: Data Management Plan 2023 - 2027.pdf

description: The data management plan of SFB-TRR 161
DOI: 10.18419/darus-4452
title: SFB/Transregio 161 Data Management Plan 2023-2027

description: &lt;p&gt;The participating universities in SFB/Transregio 161 acknowledge the general importance of re-search data management as a vital issue for all of their work and provide increasing central sup-port for long-term accessibility and reusability of data, documentation of methods and tools and privacy protection. However, technical and organisational offerings for data management can only be effective as far as researchers are aware of them and can make informed decisions on which solution is the right one for which data, which in turn requires an overall knowledge of the types and amounts of data collected or produced in the project. Furthermore, ensuring long-term availability of data for reproducibility of research results, which is one of the key ideas be-hind the research efforts of SFB/Transregio 161 and even more important in the final funding period of the project, requires planful actions as serving data beyond the lifetime of a project involves allocation of technical and organisation resources.&lt;/p&gt;
&lt;p&gt;This data management plan (DMP) identifies the research data collected or produced in SFB/Transregio 161, assesses their value for the goals of reusability and reproducibility and states the timeframes in which SFB/Transregio 161 and/or the participating universities guarantee their future availability. It furthermore describes the technical and organisational means for storing and publishing research data which the researchers of SFB/Transregio 161 can make use of. Such means might be provided by the project and funded by DFG or by the universities. The DMP states minimum requirements for metadata that must be provided for research data, briefly ad-dresses privacy and ethics issues and provides the researchers with guidelines for GPDR-compliant handling of personal data which might be collected in the projects.&lt;/p&gt;
&lt;p&gt;The DMP is a living document and therefore will be updated as necessary.&lt;/p&gt;
DOI: 10.18419/darus-4452/2
title: Data Management Plan 2023 - 2027.docx
DOI: 10.18419/darus-4459/1
title: dolfinx_eqlb-v1.0.0.tar.gz

description: The source code of version v1.0.0
DOI: 10.18419/darus-4459
title: dolfinx_eqlb v1.0.0
title: A FEniCSx based libary for flux equilibration

description: dolfinx_eqlb is an open source library, extending FEniCSx by local flux equilibration strategies. The resulting H(div) conforming fluxes can be used for the construction of adaptive finite element solvers for the Poisson problem [1], elasticity [2][3][4] or poro-elasticity [5][6].

&lt;br&gt;
&lt;br&gt;

The flux equilibration relies on so called patches, groups of all cells, connected with one node of the mesh. On each patch a constrained minimisation problem is solved [7]. In order to improve computational efficiency, a so called semi-explicit strategy [8][9] is also implemented. The solution procedure is thereby split into two steps: An explicit determination of an H(div) function, fulfilling the minimisation constraints, followed by an unconstrained minimisation on a reduced, patch-wise ansatz space. If equilibration is applied to elasticity - stress tensors have distinct symmetry properties - an additional constrained minimisation step, after the row wise reconstruction of the tensor [3][4] is implemented.

&lt;br&gt;
&lt;br&gt;

[1] Braess, D. and Schöberl, J.: Equilibrated Residual Error Estimator for Edge Elements (2008).&lt;br&gt;

[2] Prager, W. and Synge, J. L.: Approximations in elasticity based on the concept of function space (1947).&lt;br&gt;

[3] Bertrand et al.: Weakly symmetric stress equilibration and a posteriori error estimation for linear elasticity (2021).&lt;br&gt;

[4] Bertrand et al.: Weakly symmetric stress equilibration for hyperelastic material models (2020).&lt;br&gt;

[5] Riedlbeck et al.: Stress and flux reconstruction in Biot’s poro-elasticity problem with application to a posteriori error analysis (2017).&lt;br&gt;

[6] Bertrand, F. and Starke, G.: A posteriori error estimates by weakly symmetric stress reconstruction for the Biot problem (2021).&lt;br&gt;

[7] Ern, A. and Vohralik, M.: Polynomial-Degree-Robust A Posteriori Estimates in a Unified Setting for Conforming, Nonconforming, Discontinuous Galerkin, and Mixed Discretizations (2015).&lt;br&gt;

[8] Cai, Z. and Zhang, S.: Robust equilibrated residual error estimator for diffusion problems: conforming elements (2012).&lt;br&gt;
description: The instalation of dolfinx_eqlb is decribed on 
github. The easiest way is the creation of a Docker container. Alternatively, a copy of the the docker image of dolfinx_eqlb is provided within this repository. In order to use it, download the .tar.gz archive, navigate into the folder where the download is located and run

<pre>
$ cd "patch_to_folder"
$ docker load --input dockerimage-dolfinx_eqlb-v1.0.0.tar.gz
</pre>

Use persistent identifiers from Software Heritage (
 
) to cite individual files or even lines of the source code.
DOI: 10.18419/darus-4459/2
title: dockerimage-dolfinx_eqlb-v1.0.0.tar.gz

description: The Docker container of dolfinx_eqlb of version v1.0.0
DOI: 10.18419/darus-4479/1
title: dolfinx_eqlb-1.1.0.tar.gz

description: The source code of version v1.1.0
DOI: 10.18419/darus-4479
title: dolfinx_eqlb v1.1.0
title: A FEniCSx based libary for flux equilibration

description: dolfinx_eqlb is an open source library, extending FEniCSx by local flux equilibration strategies. The resulting H(div) conforming fluxes can be used for the construction of adaptive finite element solvers for the Poisson problem [1], elasticity [2][3][4] or poro-elasticity [5][6].

&lt;br&gt;
&lt;br&gt;

The flux equilibration relies on so called patches, groups of all cells, connected with one node of the mesh. On each patch a constrained minimisation problem is solved [7]. In order to improve computational efficiency, a so called semi-explicit strategy [8][9] is also implemented. The solution procedure is thereby split into two steps: An explicit determination of an H(div) function, fulfilling the minimisation constraints, followed by an unconstrained minimisation on a reduced, patch-wise ansatz space. If equilibration is applied to elasticity - stress tensors have distinct symmetry properties - an additional constrained minimisation step, after the row wise reconstruction of the tensor [3][4] is implemented.

&lt;br&gt;
&lt;br&gt;

[1] Braess, D. and Schöberl, J.: Equilibrated Residual Error Estimator for Edge Elements (2008).&lt;br&gt;

[2] Prager, W. and Synge, J. L.: Approximations in elasticity based on the concept of function space (1947).&lt;br&gt;

[3] Bertrand et al.: Weakly symmetric stress equilibration and a posteriori error estimation for linear elasticity (2021).&lt;br&gt;

[4] Bertrand et al.: Weakly symmetric stress equilibration for hyperelastic material models (2020).&lt;br&gt;

[5] Riedlbeck et al.: Stress and flux reconstruction in Biot’s poro-elasticity problem with application to a posteriori error analysis (2017).&lt;br&gt;

[6] Bertrand, F. and Starke, G.: A posteriori error estimates by weakly symmetric stress reconstruction for the Biot problem (2021).&lt;br&gt;

[7] Ern, A. and Vohralik, M.: Polynomial-Degree-Robust A Posteriori Estimates in a Unified Setting for Conforming, Nonconforming, Discontinuous Galerkin, and Mixed Discretizations (2015).&lt;br&gt;

[8] Cai, Z. and Zhang, S.: Robust equilibrated residual error estimator for diffusion problems: conforming elements (2012).&lt;br&gt;
description: The instalation of dolfinx_eqlb is decribed on 
github. The easiest way is the creation of a Docker container. Alternatively, a copy of the the docker image of dolfinx_eqlb is provided within this repository. In order to use it, download the .tar.gz archive, navigate into the folder where the download is located and run

<pre>
$ cd "patch_to_folder"
$ docker load --input dockerimage-dolfinx_eqlb-v1.1.0.tar.gz
</pre>

Use persistent identifiers from Software Heritage ( 
 
 ) to cite individual files or even lines of the source code.
DOI: 10.18419/darus-4479/2
title: dockerimage-dolfinx_eqlb-v1.1.0.tar.gz

description: The Docker container of dolfinx_eqlb of version v1.1.0
DOI: 10.18419/darus-622
title: Query sequences for the update of the ExED
title: Query sequences for the update of the Expansin Engineering Database

description: Query sequences for the individual BLAST searches used to update the Expansin Engineering Database (ExED, &lt;a href="https://exed.biocatnet.de/"&gt;https://exed.biocatnet.de/&lt;/a&gt;).
DOI: 10.18419/darus-622/1
title: Update_2_Centroids_USEARCH.fasta

description: Seed (query) sequences for the first update of the ExED (USEARCH centroid sequences). Protein sequences are given in FASTA format with one line per sequence. Headers correspond to sequence identifiers of the Expansin Engineering Database.
DOI: 10.18419/darus-622/2
title: Update_2_Centroids_USEARCH.tab

description: Tabular file with headers: sequence identifier from the Expansin Engineering Database (1st column) and NCBI accession.version (2nd column). This file lists the sequence accessions used in the first update of the ExED.
DOI: 10.18419/darus-622/3
title: Update_1_Seed_sequences_Hfams_1-25.fasta

description: Seed (query) sequences for the initial setup of the ExED. Protein sequences are given in FASTA format. Headers correspond to sequence identifiers in the style of UniprotKB.
DOI: 10.18419/darus-802/1
title: ELYSs_60_percent_identity_cutoff.graphml

description: Protein sequence network for the endolysin domains from the Glycoside Hydrolase 19 Engineering Database.
The GraphML file contains representative nodes (clustered by 90% in USEARCH) connected by at least 60% pairwise sequence identity (edge weights derived from Needleman-Wunsch alignments).
DOI: 10.18419/darus-802/2
title: GH19_40_percent_identity_cutoff.graphml

description: Protein sequence network for representative GH19 domains (corresponding to Pfam’s GH19 profile HMM: PF00182) from the Glycoside Hydrolase 19 Engineering Database. The GraphML file contains representative nodes (clustered by 90% in USEARCH) connected by at least 40% pairwise sequence identity (edge weights derived from Needleman-Wunsch alignments).
DOI: 10.18419/darus-802/3
title: CHITs_60_percent_identity_cutoff.graphml

description: Protein sequence network for the chitinase domains from the Glycoside Hydrolase 19 Engineering Database.
The GraphML file contains representative nodes (clustered by 90% in USEARCH) connected by at least 60% pairwise sequence identity (edge weights derived from Needleman-Wunsch alignments).
DOI: 10.6084/m9.figshare.27637434.v1
title: Summary of descriptive statistics

description: The descriptive statistics of the data.
DOI: 10.15468/dl.mva9yg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Apus apus (Linnaeus, 1758)",
 "Year is 22",
 "Country is Netherlands"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003369-241107131044228/datasets/export for details.
DOI: 10.18419/darus-866/1
title: projections.tar

description: Projection images (360 deg, angle increment 0.25 deg), dark image (di) and open beam image (ob) in 16 bit *.tif file format.
DOI: 10.18419/darus-866/2
title: processed.tar

description: This dataset is the transformed, cutted and processed version of the XRCT images. It contains the 20 binarized slices with the precipitates flagged as 1.
The size of the volume is 89 mm x 22 mm x 0.085 mm.
DOI: 10.18419/darus-1996/1
title: ListStuttgartGyroCollection_Inv.Nr.pdf
DOI: 10.18419/darus-1996/2
title: GyrologDatarepositoryStructure.pdf
DOI: 10.18419/darus-1996/3
title: 2D Workflow.pdf
DOI: 10.18419/darus-821
title: Information about the Gyrolog data repository

description: &lt;p&gt;The three pdf-files contain some information about the digitisation strategy for all objects, about the structure of the data repository, and about the inventory of the primary gyro collection in Stuttgart.&lt;/p&gt; 

For more information see the &lt;a href="https://digibus.ub.uni-stuttgart.de/viewer/kreiselsammlung/"&gt;digital library based on Goobi&lt;/a&gt; as well as the related publications below.
DOI: 10.18419/darus-866
title: micro-XRCT dataset of Enzymatically Induced Calcite Precipitation (EICP) in a microfluidic cell

description: micro-XRCT dataset (projection and reconstructed images) based on a region of interest scan (diameter 12.49 mm, height 9.09 mm) of a microfluidic cell including calcium carbonate aggregates along with the processed dataset (cropped, transformed and binarized).
DOI: 10.18419/darus-866/3
title: reconstructed.tar

description: Reconstructed micro-XRCT data set in 16 bit *.tif file format. 2940x2940x2139 voxels with the uniform voxel size of 4.24 µm.
DOI: 10.18419/darus-1030/1
title: 01_DSC00125.tif
DOI: 10.18419/darus-1030/2
title: 03_DSC00141.tif
DOI: 10.18419/darus-1030
title: 2D pictures of KK17/2-09

description: &lt;p&gt;Dataset contains all pictures (.jpg; .arw) that were taken during the &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=49056&version=DRAFT"&gt;2D digitisation strategy&lt;/a&gt; for this object.&lt;/p&gt; &lt;p&gt;Order of data: object was digitised according to a digitisation schema visible within the Dataset&lt;/p&gt;&lt;ul&gt;&lt;li&gt;characteristic view,&lt;/li&gt; &lt;li&gt;front view,&lt;/li&gt; &lt;li&gt;left view,&lt;/li&gt; &lt;li&gt;back view,&lt;/li&gt; &lt;li&gt;right view,&lt;/li&gt;&lt;li&gt;bottom view,&lt;/li&gt; &lt;li&gt;upward view, &lt;/li&gt;&lt;li&gt;details (details 1, details 2, ..., details n)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt; This schema is indicated within the pictures by inventory label and then labels according to view.&lt;/p&gt;&lt;p&gt; Further information one can find in the document: Setting and workflow for basic development of 2D.&lt;/p&gt;&lt;p&gt;This dataset is part of the digital gyroscope collection. For more information about 
the collection and its creation, please see the documentation dataset:
&lt;i&gt;Niklaus, Maria, 2021, "Information about the Gyrolog data repository", 
&lt;a href="https://doi.org/10.18419/darus-821"&gt;doi: 10.18419/darus-821&lt;/a&gt;, DaRUS.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;To refer to the whole collection: Wagner, Jörg F.; Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Zhan, Kun, 2021, "Digital Gyroscope Collection Created by the Project 'Gyrolog'", &lt;a href="https://doi.org/10.18419/darus-gyrolog"&gt;doi: 10.18419/darus-gyrolog&lt;/a&gt;, DaRUS.&lt;/b&gt;&lt;/p&gt;
description: directional gyro
DOI: 10.18419/darus-1030/3
title: 02_DSC00131.tif
DOI: 10.18419/darus-1031/1
title: 01_DSC00141.tif
DOI: 10.18419/darus-1031/2
title: 02_DSC00131.tif
DOI: 10.18419/darus-1031
title: 2D pictures of KK17/3-09

description: &lt;p&gt;Dataset contains all pictures (.jpg; .arw) that were taken during the &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=49056&version=DRAFT"&gt;2D digitisation strategy&lt;/a&gt; for this object.&lt;/p&gt; &lt;p&gt;Order of data: object was digitised according to a digitisation schema visible within the Dataset&lt;/p&gt;&lt;ul&gt;&lt;li&gt;characteristic view,&lt;/li&gt; &lt;li&gt;front view,&lt;/li&gt; &lt;li&gt;left view,&lt;/li&gt; &lt;li&gt;back view,&lt;/li&gt; &lt;li&gt;right view,&lt;/li&gt;&lt;li&gt;bottom view,&lt;/li&gt; &lt;li&gt;upward view, &lt;/li&gt;&lt;li&gt;details (details 1, details 2, ..., details n)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt; This schema is indicated within the pictures by inventory label and then labels according to view.&lt;/p&gt;&lt;p&gt; Further information one can find in the document: Setting and workflow for basic development of 2D.&lt;/p&gt;&lt;p&gt;This dataset is part of the digital gyroscope collection. For more information about 
the collection and its creation, please see the documentation dataset:
&lt;i&gt;Niklaus, Maria, 2021, "Information about the Gyrolog data repository", 
&lt;a href="https://doi.org/10.18419/darus-821"&gt;doi: 10.18419/darus-821&lt;/a&gt;, DaRUS.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;To refer to the whole collection: Wagner, Jörg F.; Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Zhan, Kun, 2021, "Digital Gyroscope Collection Created by the Project 'Gyrolog'", &lt;a href="https://doi.org/10.18419/darus-gyrolog"&gt;doi: 10.18419/darus-gyrolog&lt;/a&gt;, DaRUS.&lt;/b&gt;&lt;/p&gt;
description: directional gyro
DOI: 10.18419/darus-1031/3
title: 01_DSC00125.tif
DOI: 10.18419/darus-1032/1
title: 03_DSC00139.tif
DOI: 10.18419/darus-1032/2
title: 02_DSC00132.tif
DOI: 10.18419/darus-1032
title: 2D pictures of KK17/4-09

description: &lt;p&gt;Dataset contains all pictures (.jpg; .arw) that were taken during the &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=49056&version=DRAFT"&gt;2D digitisation strategy&lt;/a&gt; for this object.&lt;/p&gt; &lt;p&gt;Order of data: object was digitised according to a digitisation schema visible within the Dataset&lt;/p&gt;&lt;ul&gt;&lt;li&gt;characteristic view,&lt;/li&gt; &lt;li&gt;front view,&lt;/li&gt; &lt;li&gt;left view,&lt;/li&gt; &lt;li&gt;back view,&lt;/li&gt; &lt;li&gt;right view,&lt;/li&gt;&lt;li&gt;bottom view,&lt;/li&gt; &lt;li&gt;upward view, &lt;/li&gt;&lt;li&gt;details (details 1, details 2, ..., details n)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt; This schema is indicated within the pictures by inventory label and then labels according to view.&lt;/p&gt;&lt;p&gt; Further information one can find in the document: Setting and workflow for basic development of 2D.&lt;/p&gt;&lt;p&gt;This dataset is part of the digital gyroscope collection. For more information about 
the collection and its creation, please see the documentation dataset:
&lt;i&gt;Niklaus, Maria, 2021, "Information about the Gyrolog data repository", 
&lt;a href="https://doi.org/10.18419/darus-821"&gt;doi: 10.18419/darus-821&lt;/a&gt;, DaRUS.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;To refer to the whole collection: Wagner, Jörg F.; Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Zhan, Kun, 2021, "Digital Gyroscope Collection Created by the Project 'Gyrolog'", &lt;a href="https://doi.org/10.18419/darus-gyrolog"&gt;doi: 10.18419/darus-gyrolog&lt;/a&gt;, DaRUS.&lt;/b&gt;&lt;/p&gt;
description: directional gyro
DOI: 10.18419/darus-1032/3
title: 01_DSC00125.tif
DOI: 10.18419/darus-4437/1
title: Website Introduction .pdf
DOI: 10.18419/darus-4437
title: COLife_05: Gigamap and Game Introduction

description: The dataset presents two files: A game design introduction and the gigamap that led to its design. The design introduction has led to the implementation of the game on the following &lt;a href="https://colifebiodiversity.wixsite.com/co-life-1"&gt;&lt;b&gt;Website&lt;/b&gt;&lt;/a&gt;. The game is to engage the urban citizens to support their local biodiversity by making DIY recipes or sharing photos of how they support it. The gigamap is a process tool that led the project to the competition and represents its codesigning processes across multiple stakeholders.
DOI: 10.18419/darus-4437/2
title: Gigamap.pdf
DOI: 10.18419/darus-1033/1
title: 03_DSC00139.tif
DOI: 10.18419/darus-1033/2
title: 01_DSC00125.tif
DOI: 10.18419/darus-1033
title: 2D pictures of KK17/5-09

description: &lt;p&gt;Dataset contains all pictures (.jpg; .arw) that were taken during the &lt;a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=49056&version=DRAFT"&gt;2D digitisation strategy&lt;/a&gt; for this object.&lt;/p&gt; &lt;p&gt;Order of data: object was digitised according to a digitisation schema visible within the Dataset&lt;/p&gt;&lt;ul&gt;&lt;li&gt;characteristic view,&lt;/li&gt; &lt;li&gt;front view,&lt;/li&gt; &lt;li&gt;left view,&lt;/li&gt; &lt;li&gt;back view,&lt;/li&gt; &lt;li&gt;right view,&lt;/li&gt;&lt;li&gt;bottom view,&lt;/li&gt; &lt;li&gt;upward view, &lt;/li&gt;&lt;li&gt;details (details 1, details 2, ..., details n)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt; This schema is indicated within the pictures by inventory label and then labels according to view.&lt;/p&gt;&lt;p&gt; Further information one can find in the document: Setting and workflow for basic development of 2D.&lt;/p&gt;&lt;p&gt;This dataset is part of the digital gyroscope collection. For more information about 
the collection and its creation, please see the documentation dataset:
&lt;i&gt;Niklaus, Maria, 2021, "Information about the Gyrolog data repository", 
&lt;a href="https://doi.org/10.18419/darus-821"&gt;doi: 10.18419/darus-821&lt;/a&gt;, DaRUS.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;&lt;b&gt;To refer to the whole collection: Wagner, Jörg F.; Ceranski, Beate; Fritsch, Dieter; Mammadov, Gasim; Niklaus, Maria; Schweizer, Timo; Simon, Sven; Zhan, Kun, 2021, "Digital Gyroscope Collection Created by the Project 'Gyrolog'", &lt;a href="https://doi.org/10.18419/darus-gyrolog"&gt;doi: 10.18419/darus-gyrolog&lt;/a&gt;, DaRUS.&lt;/b&gt;&lt;/p&gt;
description: directional gyro
DOI: 10.18419/darus-1033/3
title: 02_DSC00132.tif
DOI: 10.5518/1297
title: Modelling and breaking down the biophysical barriers to drug delivery in pancreatic cancer 

description: The dataset are of raw images and collated data. The raw images are of subsequent assessment of the microfluidic PDAC cultures using a bright-field, epi-fluorescence, and confocal microscopy. The collated data are of the viability assessments, immunofluorescence assessmetns, of the microfluidic PDAC cultures following treatment with gemcitabine and losartan, and of the interstitial flow assessments.