The CytoData society (CytoDS) builds and maintains an active community around image-based profiling of biological phenotypes induced by genetic, chemical or other perturbations of biological systems.
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Should be a current board member. The candidate nominates theirself by emailing the President. The President then sends out a list to the Board to vote on. If it’s a tie, the President decides.
Anyone can nominate themselves, or others (in which case the board will confirm their interest) by emailing cytodata.info@gmail.com. The nominee provides a 3-sentence summary of qualifications and interest, and the Communication Officer send out a list for the Society to vote on. Majority of votes wins; if it’s a tie the Board will vote.
CytoDS will grant the use of its name and its full support to the organization of an annual scientific meeting of the image-based profiling research community. The purpose of these meetings is discussing recent advances in the field and fostering communication within the research community. Connections with other domains are forge by inviting experts from those fields to give a presentation at the symposium. The agenda is created by the organizers, while CytoDS will assist in fundraising, outreach and general organizational questions. The location of the meeting should be chosen based on an online poll sent to all members of the society, and must adhere to the equal rights policies of the society.
To push the limits of current and nurture the development of new cutting edge computational methods for analysis of image-based profiling experiments, CytoDS will assist in the organization of Hackathons. These can, but not have to, be connected to the annual conferences of the image-based profiling community. The content shall be decided by the organizers, but CytoDS will lend its name and assistance in fundraising, outreach and general organizational questions. The location of the Hackathon should vary each time and it must adhere to the equal rights policies of the society.
The visibility of CytoDS will be provided by a shared web-presence. The presence may be hosted in the public domain and shall be accessible freely for anybody. The web presence represents the society and all its members. It provides a framework for showcasing the societies activities and provides a framework for all other related web-hosted communication (e.g. forums).
CytoDS aims to connect researchers worldwide in a vibrant community with many open opportunities to share and discuss ideas. Thus, in order to bridge geographical distances there should be a actively maintained web-based internet presence and community forum for scientific exchange. The forums and e-mail lists shall be moderated such that it is ensured everybody obeys to the values of CytoDS and the policies of good scientific practice. The forums can be hosted via public-corporate platforms or the societies own web-domain. Voluntary commitment of the societies members will ensure long-term sustained maintenance of the forum such that also its history does not get lost, when e.g. technology changes.
To foster wide adoption and broad applications of results from research on image-based profiling methods, CytoDS aims to create open communication channels between academia and industrial partners. Researchers from both, industry as well as academia, are encouraged to contribute to discussions and participate in meetings.
While CytoDS aims to foster new technologies, it also sets out to actively pass down the current state of the art to the next generation of scientists.To this end, it actively seeks early career researchers to contribute to running the society. As well, members of the society are encouraged to reach out the next generation to raise awareness of the societies actions, meetings, and knowledge collections (e.g. web-resource collections). Hackathons and workshops during scientific meeting organized by CytoDS should further increase the accessibility of image-based profiling research.
We aim to draw in other researchers from various different communities whose techniques / knowledge might be profitably applied to the field of image based profiling. This will ultimately lead to the mutual benefit of all communities and brings all research areas a step forward.
Although some techniques from these fields, such as image filtering/preprocessing or feature extraction are readily applied to image-based profiling data, the high dimensional structure of image-based data demands that this community develop new techniques that exploit the multivariate nature of image information to gain new biological insights.
Currently, the L1000 transcriptional profiling assay is the only viable technology in this space. Image-based profiling data presents this community the opportunity to add a complementary data source and methods. developed by the L1000 community to the field of image-based profiling.
The high-content screening community has several decades of experience in running large image-based experiments. Currently, nearly all image-based profiling datasets are likely generated by individuals who identify as part of this community. Their inputs on planning large-scale experiments, handling batch effects, and interfacing with other groups when executing a project, can provide invaluable inputs to inform the data analysis performed downstream.
Due to the enormous amount of data produced during an image based high-throughput experiment this community also builds on a shared knowledge base of how to handle, analyze and make sense of terabytes of data from single experiments, particularly at the single-cell level. This can be invaluable for other communities just starting with data production of such dimensions (e.g. single-cell sequencing and transcriptomics).
CytoData will not file for non-profit status and will not manage funds. Instead, each year, the symposium organizers will come up with a proposal and the committee will give permission to use the CytoData name.
The symposium strategy will be revisited each year.
(Pending)
(Pending)
We are maintaining a list of interesting papers in the field via https://github.com/cytodata/awesome-cytodata