Excemplify: A Flexible Template Based Solution, Parsing and Managing Data in Spreadsheets for Experimentalists

Shi, Lei; Jong, Lenneke M.; Wittig, Ulrike; Lucarelli, Philippe; Stepath, Markus; Mueller, Stephanie; D'alessandro, L; Klingmüller, Ursula; Müller, Wolfgang G.

doi:10.1515/jib-2013-220

Cited by 3 publications

(5 citation statements)

References 14 publications

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Section: Methodsmentioning

confidence: 99%

“…The raw data of all qualitative and quantitative immunoblots of this work can be accessed as Source Data for the respective figure. Data of quantified immunoblots have also been uploaded through Excemplify (Shi et al, 2013) to the SEEK platform (http://seek.sbe po.de/; Wolstencroft et al, 2015) and FAIRDOMHub (https://faird omhub.org/). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (Vizcaíno et al, 2016) partner repository with the dataset identifier PXD004816.…”

Section: Time Course Experiments Cell Lysis Quantitative Immunoblotmentioning

confidence: 99%

Section: Time Course Experiments Cell Lysis Quantitative Immunoblotti...mentioning

confidence: 99%

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Protein abundance of AKT and ERK pathway components governs cell type‐specific regulation of proliferation

Adlung

Kar

Wagner

et al. 2017

Molecular Systems Biology

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Signaling through the AKT and ERK pathways controls cell proliferation. However, the integrated regulation of this multistep process, involving signal processing, cell growth and cell cycle progression, is poorly understood. Here, we study different hematopoietic cell types, in which AKT and ERK signaling is triggered by erythropoietin (Epo). Although these cell types share the molecular network topology for pro‐proliferative Epo signaling, they exhibit distinct proliferative responses. Iterating quantitative experiments and mathematical modeling, we identify two molecular sources for cell type‐specific proliferation. First, cell type‐specific protein abundance patterns cause differential signal flow along the AKT and ERK pathways. Second, downstream regulators of both pathways have differential effects on proliferation, suggesting that protein synthesis is rate‐limiting for faster cycling cells while slower cell cycles are controlled at the G1‐S progression. The integrated mathematical model of Epo‐driven proliferation explains cell type‐specific effects of targeted AKT and ERK inhibitors and faithfully predicts, based on the protein abundance, anti‐proliferative effects of inhibitors in primary human erythroid progenitor cells. Our findings suggest that the effectiveness of targeted cancer therapy might become predictable from protein abundance.

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Section: Methodsmentioning

confidence: 99%

Section: Time Course Experiments Cell Lysis Quantitative Immunoblotmentioning

confidence: 99%

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Protein abundance of AKT and ERK pathway components governs cell type‐specific regulation of proliferation

Adlung

Kar

Wagner

et al. 2017

Molecular Systems Biology

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“…Here, methods for comprehensive data annotation in spreadsheets using, for example, rightfield or in SBML files using semanticsbml could support the integration process. The tool excemplify is built to create rightfield ‐compatible templates at the same time as helping experimentalists with the handling of experimental data. Thus, even preliminary data that are likely to be discarded later can be enriched using metadata of the experiments compliant with definitions in ontologies and controlled vocabularies.…”

Section: Standardization Initiatives and Toolsmentioning

confidence: 99%

Challenges for an enzymatic reaction kinetics database

et al. 2013

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The scientific literature contains a tremendous amount of kinetic data describing the dynamic behaviour of biochemical reactions over time. These data are needed for computational modelling to create models of biochemical reaction networks and to obtain a better understanding of the processes in living cells. To extract the knowledge from the literature, biocurators are required to understand a paper and interpret the data. For modellers, as well as experimentalists, this process is very time consuming because the information is distributed across the publication and, in most cases, is insufficiently structured and often described without standard terminology. In recent years, biological databases for different data types have been developed. The advantages of these databases lie in their unified structure, searchability and the potential for augmented analysis by software, which supports the modelling process. We have developed the SABIO-RK database for biochemical reaction kinetics. In the present review, we describe the challenges for database developers and curators, beginning with an analysis of relevant publications up to the export of database information in a standardized format. The aim of the present review is to draw the experimentalist's attention to the problem (from a data integration point of view) of incompletely and imprecisely written publications. We describe how to lower the barrier to curators and improve this situation. At the same time, we are aware that curating experimental data takes time. There is a community concerned with making the task of publishing data with the proper structure and annotation to ontologies much easier. In this respect, we highlight some useful initiatives and tools.

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“…Several prior tools have attempted to bridge this gap with respect to experiment metadata by offering more user-friendly approaches to annotation with semantic information ( e.g. , RightField, Excemplify, and the CEDAR workbench). All of these tools, however, are focused on the definition of terms rather than representing the larger-scale design of an experiment.…”

Section: Introductionmentioning

confidence: 99%

Intent Parser: A Tool for Codification and Sharing of Experimental Design

et al. 2021

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Communicating information about experimental design among a team of collaborators is challenging because different people tend to describe experiments in different ways and with different levels of detail. Sometimes, humans can interpret missing information by making assumptions and drawing inferences from information already provided. Doing so, however, is error-prone and typically requires a high level of interpersonal communication. In this paper, we present a tool that addresses this challenge by providing a simple interface for incremental formal codification of experiment designs. Users interact with a Google Docs word-processing interface with structured tables, backed by assisted linking to machine-readable definitions in a data repository (SynBioHub) and specification of available protocols and requests for execution in the Open Protocol Interface Language (OPIL). The result is an easy-to-use tool for generating machine-readable descriptions of experiment designs with which users in the DARPA SD2 program have collected data from 80 208 samples using a variety of protocols and instruments over the course of 181 experiment runs.

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Excemplify: A Flexible Template Based Solution, Parsing and Managing Data in Spreadsheets for Experimentalists

Cited by 3 publications

References 14 publications

Protein abundance of AKT and ERK pathway components governs cell type‐specific regulation of proliferation

Protein abundance of AKT and ERK pathway components governs cell type‐specific regulation of proliferation

Challenges for an enzymatic reaction kinetics database

Intent Parser: A Tool for Codification and Sharing of Experimental Design

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