FaceBase: A Community-Driven Hub for Data-Intensive Research
Abstract
The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository and educational resources exemplify the FAIR principles and support a broad user community including researchers in craniofacial development, molecular genetics, and genomics. FaceBase demonstrates that a model in which researchers “self-curate” their data can be successful and scalable. We present the results of the first 2.5 y of FaceBase’s operations as an open community and summarize the data sets published during this period. We then describe a research highlight from work on the identification of regulatory networks and noncoding RNAs involved in cleft lip with/without cleft palate that both used and in turn contributed new findings to publicly available FaceBase resources. Collectively, FaceBase serves as a dynamic and continuously evolving resource to facilitate data-intensive research, enhance data reproducibility, and perform deep phenotyping across multiple species in dental and craniofacial research.
Get full access to this article
View all access and purchase options for this article.
Data availability statement
All data are available at https://www.facebase.org. Data listed in the Table may be found by their respective DOI as indicated.
References
Beaty TH, Marazita ML, Leslie EJ. 2016. Genetic factors influencing risk to orofacial clefts: today’s challenges and tomorrow’s opportunities. F1000Res. 5:2800.
Brinkley JF, Borromeo C, Clarkson M, Cox TC, Cunningham MJ, Detwiler LT, Heike CL, Hochheiser H, Mejino JLV, Travillian RS, et al. 2013. The ontology of craniofacial development and malformation for translational craniofacial research. Am J Med Genet C. 163(4):232–245.
Brinkley JF, Fisher S, Harris MP, Holmes G, Hooper JE, Jabs EW, Jones KL, Kesselman C, Klein OD, Maas RL, et al. 2016. The FaceBase Consortium: a comprehensive resource for craniofacial researchers. Development. 143(14):2677–2688.
Bugacov A, Czajkowski K, Kesselman C, Kumar A, Schuler RE, Tangmunarunkit H. 2017. Experiences with DERIVA: an asset management platform for accelerating escience. 2017 IEEE 13th International Conference on E-Science (E-Science); Auckland, New Zealand. New York (NY): IEEE. p. 79–88.
Chard K, D’Arcy M, Heavner B, Foster I, Kesselman C, Madduri R, Rodriguez A, Soliland-Reyes S, Goble C, Clark K, et al. 2016. I’ll take that to go: big data bags and minimal identifiers for exchange of large, complex datasets. IEEE International Conference on Big Data. New York (NY): IEEE. p. 319–328.
Curino CA, Moon HJ, Ham M, Zaniolo C. 2009. The PRISM workwench: database schema evolution without tears. ICDE: 2009 IEEE 25th International Conference on Data Engineering; Shanghai, China. New York (NY): IEEE. p. 1523–1526.
Czajkowski K, Kesselman C, Schuler RE, Tangmunarunkit H. 2018. ERMrest: a web service for collaborative data management. 30th International Conference on Scientific and Statistical Database Management (SSDBM 2018); July, 2018; Bozen-Bolzano Italy. ACM. p. 1–12.
Dempsey W, Foster I, Fraser S, Kesselman C. 2022. Sharing begins at home. arXiv 2201.06564v1. https://arxiv.org/abs/2201.06564.
Dixon MJ, Marazita ML, Beaty TH, Murray JC. 2011. Cleft lip and palate: understanding genetic and environmental influences. Nat Rev Genet. 12(3):167–178.
Fu Q, Liu CJ, Zhai ZS, Zhang X, Qin T, Zhang HW. 2018. Single-cell non-coding RNA in embryonic development. Adv Exp Med Biol. 1068:19–32.
Gajera M, Desai N, Suzuki A, Li A, Zhang M, Jun G, Jia P, Zhao Z, Iwata J. 2019. MicroRNA-655-3p and microRNA-497-5p inhibit cell proliferation in cultured human lip cells through the regulation of genes related to human cleft lip. BMC Med Genomics. 12(1):70.
Gil N, Ulitsky I. 2020. Regulation of gene expression by cis-acting long non-coding RNAs. Nat Rev Genet. 21(2):102–117.
Hudder A, Novak RF. 2008. MiRNAs: effectors of environmental influences on gene expression and disease. Toxicol Sci. 103(2):228–240.
International Society for Biocuration. 2018. Biocuration: distilling data into knowledge. PLoS Biol. 16(4):e2002846.
Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, Zahler AM, Haussler D. 2002. The human genome browser at UCSC. Genome Res. 12(6):996–1006.
Li A, Jia P, Mallik S, Fei R, Yoshioka H, Suzuki A, Iwata J, Zhao Z. 2020. Critical microRNAs and regulatory motifs in cleft palate identified by a conserved miRNA-TF-gene network approach in humans and mice. Brief Bioinform. 21(4):1465–1478.
Li A, Qin G, Suzuki A, Gajera M, Iwata J, Jia P, Zhao Z. 2019. Network-based identification of critical regulators as putative drivers of human cleft lip. BMC Med Genomics. 12(Suppl 1):16.
Mungall CJ, Torniai C, Gkoutos GV, Lewis SE, Haendel MA. 2012. Uberon, an integrative multi-species anatomy ontology. Genome Biol. 13(1):R5.
Roundtree IA, He C. 2016. RNA epigenetics—chemical messages for posttranscriptional gene regulation. Curr Opin Chem Biol. 30:46–51.
Saltzer JH, Reed DP, Clark DD. 1984. End-to-end arguments in system-design. ACM Trans Comput Syst. 2(4):277–288.
Samuels BD, Aho R, Brinkley JF, Bugacov A, Feingold E, Fisher S, Gonzalez-Reiche AS, Hacia JG, Hallgrimsson B, Hansen K, et al. 2020. FaceBase 3: analytical tools and fair resources for craniofacial and dental research. Development. 147(18):dev191213.
Schuler R, Bugacov A, Blow M, Kesselman C. 2019. Toward FAIR knowledge turns in bioinformatics. IEEE International Conference on Bioinformatics and Biomedicine (BIBM); San Diego, CA. New York (NY): IEEE. p. 1240–1242.
Schuler R, Czajkowski K, D’Arcy M, Tangmunarunkit H, Kesselman C. 2020. Towards co-evolution of data-centric ecosystems. 32nd International Conference on Scientific and Statistical Database Management; July 7–9, 2020; New York, NY. ACM. Vol. 4. p. 1–12.
Schuler RE, Kesselman C, Czajkowski K. 2016. Accelerating data-driven discovery with scientific asset management. The IEEE 12th International Conference on eScience; Baltimore, MD. New York (NY): IEEE. p. 31–40.
Smith CL, Eppig JT. 2009. The mammalian phenotype ontology: enabling robust annotation and comparative analysis. Wires Syst Biol Med. 1(3):390–399.
Speir ML, Bhaduri A, Markov NS, Moreno P, Nowakowski TJ, Papatheodorou I, Pollen AA, Raney BJ, Seninge L, Kent WJ, et al. 2021. UCSC cell browser: visualize your single-cell data. Bioinformatics. 37(23):4578–4580.
Stonebraker M, Deng D, Brodie ML. 2016. Database decay and how to avoid it. IEEE International Conference on Big Data (Big Data); Washington, DC. New York (NY): IEEE. p. 7–16.
Suzuki A, Abdallah N, Gajera M, Jun G, Jia P, Zhao Z, Iwata J. 2018. Genes and microRNAs associated with mouse cleft palate: a systematic review and bioinformatics analysis. Mech Dev. 150:21–27.
Suzuki A, Li A, Gajera M, Abdallah N, Zhang M, Zhao Z, Iwata J. 2019. MicroRNA-374a, -4680, and -133b suppress cell proliferation through the regulation of genes associated with human cleft palate in cultured human palate cells. BMC Med Genomics. 12(1):93.
Suzuki A, Sangani DR, Ansari A, Iwata J. 2016. Molecular mechanisms of midfacial developmental defects. Dev Dyn. 245(3):276–293.
Tangmunarunkit H, Shafaeibejestan A, Chudy J, Czajkowski K, Schuler R, Kesselman C. 2021. Model-adaptive interface generation for data-driven discovery. CoRR. abs/2110.01781. https://arxiv.org/abs/2110.01781 arXiv preprint.
Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, et al. 2016. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 3:160018.
Xu HD, Yan FF, Hu RF, Suzuki A, Iwaya C, Jia PL, Iwata J, Zhao ZM. 2021. CleftGeneDB: a resource for annotating genes associated with cleft lip and cleft palate. Sci Bull. 66(23):2340–2342.
Yan F, Jia P, Yoshioka H, Suzuki A, Iwata J, Zhao Z. 2020. A developmental stage-specific network approach for studying dynamic co-regulation of transcription factors and microRNAs during craniofacial development. Development. 147(24):dev192948.
Yoshioka H, Mikami Y, Ramakrishnan SS, Suzuki A, Iwata J. 2021. MicroRNA-124-3p plays a crucial role in cleft palate induced by retinoic acid. Front Cell Dev Biol. 9:621045.
Yoshioka H, Ramakrishnan SS, Shim J, Suzuki A, Iwata J. 2021. Excessive all-trans retinoic acid inhibits cell proliferation through upregulated microRNA-4680-3p in cultured human palate cells. Front Cell Dev Biol. 9:618876.
Yoshioka H, Ramakrishnan SS, Suzuki A, Iwata J. 2021. Phenytoin inhibits cell proliferation through microRNA-196a-5p in mouse lip mesenchymal cells. Int J Mol Sci. 22(4):1746.
Cite article
Cite article
Cite article
OR
Download to reference manager
If you have citation software installed, you can download article citation data to the citation manager of your choice
Information, rights and permissions
Information
Published In
Article first published online: July 31, 2022
Issue published: October 2022
Keywords
Data availability statement
Data is available for this article. View more information
PubMed: 35912790
Authors
Metrics and citations
Metrics
Article usage*
Total views and downloads: 534
*Article usage tracking started in December 2016
Altmetric
See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores
Articles citing this one
Receive email alerts when this article is cited
Web of Science: 3 view articles Opens in new tab
Crossref: 1
- Data-Driven Dental, Oral, and Craniofacial Analytics: Here to Stay
Figures and tables
Figures & Media
Tables
View Options
Access options
If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:
I am signed in as:
View my profileSign out
I can access personal subscriptions, purchases, paired institutional access and free tools such as favourite journals, email alerts and saved searches.
loading institutional access options
Alternatively, view purchase options below:
Purchase 24 hour online access to view and download content.
Access journal content via a DeepDyve subscription or find out more about this option.
