Sharing and reusing cell image data

Abstract

The rapid growth in content and complexity of cell image data creates an opportunity for synergy between experimental and computational scientists. Sharing microscopy data enables computational scientists to develop algorithms and tools for data analysis, integration, and mining. These tools can be applied by experimentalists to promote hypothesis-generation and discovery. We are now at the dawn of this revolution: infrastructure is being developed for data standardization, deposition, sharing, and analysis; some journals and funding agencies mandate data deposition; data journals publish high-content microscopy data sets; quantification becomes standard in scientific publications; new analytic tools are being developed and dispatched to the community; and huge data sets are being generated by individual labs and philanthropic initiatives. In this Perspective, I reflect on sharing and reusing cell image data and the opportunities that will come along with it.

Data Reuse and the Social Capital of Open Science

“…In open data sharing, exchange does not revolve around a single currency, but rather revolves around instances of social capital. In [48], it is suggested that a credit and incentives system can be established through various social signals and time-saving guarantees. Social incentives for sharing data can involve the currency of status-seeking through authorship [48], endorsement by an authority in a given discipline [49], or rewarding citation counts for a shared data set [50].…”

“…In [48], it is suggested that a credit and incentives system can be established through various social signals and time-saving guarantees. Social incentives for sharing data can involve the currency of status-seeking through authorship [48], endorsement by an authority in a given discipline [49], or rewarding citation counts for a shared data set [50]. As part of a virtuous cycle, the practice of open data sharing itself can serve to increase the credibility of research articles and their authors [41].…”

Community Standards for Open Cell Migration Data

“…To enable cell migration data integration, mining and meta-analysis, we initiated an open data exchange ecosystem for cell migration research 6 . The aim was to overcome the current fragmentation of cell migration research and facilitate data exchange, dissemination, verification, interoperability and reuse, as well as encourage data sharing 7 . This should also increase the reproducibility of experiments, enable data mining and meta-analyses, and thus satisfy the FAIR principles for Findable, Accessible, Interoperable and Reusable data 8 .…”

Protein interactions of Magnaporthe oryzae protein kinase CK2 and secondary data analysis of a large number of transcriptomes suggest chaperone-like activity is integral to its function

“…Interestingly, intrinsically highly disordered SRP40 protein in 43 yeast (homologous to Nopp140; Insect, Drosophila and Nolc1;Mammal, Human) has been shown to 44 become phosphorylated to varying degrees by CK2 with effects on the SRP40 conformation, binding, 45 and aggregation properties with further effects on the diverse functions of the protein (Tantos et al, 46 2013; Na et al, 2018). The large number of substrates of CK2, could possibly be explained if CK2 47To test this destabilization/unfolding hypothesis in a general way we decided to make an analysis of 64 secondary data already published (Smith et al, 2011;Zaritsky, 2018) and downloaded a large range of 65 transcriptomic data for M. oryzae. The following hypotheses resulting from the general hypothesis 66 were tested: Sub-hypothesis 1: If unfolding-refolding activity is important for IDP aggregation then a 67 high CKa expression should be correlated with expression of some S/T phosphatases present in the 68 pulldown that can act as a counterpart to the CK2 S/T kinase activity.…”

“…To test this destabilization/unfolding hypothesis in a general way we decided to make an analysis of 64 secondary data already published (Smith et al, 2011;Zaritsky, 2018) and downloaded a large range of 65 transcriptomic data for M. oryzae. The following hypotheses resulting from the general hypothesis 66 were tested: Sub-hypothesis 1: If unfolding-refolding activity is important for IDP aggregation then a 67 high CKa expression should be correlated with expression of some S/T phosphatases present in the 68 pulldown that can act as a counterpart to the CK2 S/T kinase activity.…”