1. Roddy, Jack W and Lesica, George T and Wheeler, Travis J (2022) {{SODA}}: A {{TypeScript}}/{{JavaScript}} Library for Visualizing Biological Sequence Annotation. NAR Genomics and Bioinformatics 4(4): lqac077 https://doi.org/10.1093/nargab/lqac077, /Users/nishad/Zotero/storage/CTH6BQ5L/Roddy et al. - 2022 - SODA a TypeScriptJavaScript library for visualiz.pdf;/Users/nishad/Zotero/storage/B2TTVVTQ/6749379.html, We present SODA, a lightweight and open-source visualization library for biological sequence annotations that enables straightforward development of flexible, dynamic and interactive web graphics. SODA is implemented in TypeScript and can be used as a library within TypeScript and JavaScript., https://doi.org/10.1093/nargab/lqac077, 2631-9268, December, {{SODA}}
2. Neves, Mariana and Ševa, Jurica (2019) An extensive review of tools for manual annotation of documents. Briefings in Bioinformatics 22(1): 146 –163 https://doi.org/10.1093/bib/bbz130, December, Annotation tools are applied to build training and test corpora, which are essential for the development and evaluation of new natural language processing algorithms. Further, annotation tools are also used to extract new information for a particular use case. However, owing to the high number of existing annotation tools, finding the one that best fits particular needs is a demanding task that requires searching the scientific literature followed by installing and trying various tools.We searched for annotation tools and selected a subset of them according to five requirements with which they should comply, such as being Web-based or supporting the definition of a schema. We installed the selected tools (when necessary), carried out hands-on experiments and evaluated them using 26 criteria that covered functional and technical aspects. We defined each criterion on three levels of matches and a score for the final evaluation of the tools.We evaluated 78 tools and selected the following 15 for a detailed evaluation: BioQRator, brat, Catma, Djangology, ezTag, FLAT, LightTag, MAT, MyMiner, PDFAnno, prodigy, tagtog, TextAE, WAT-SL and WebAnno. Full compliance with our 26 criteria ranged from only 9 up to 20 criteria, which demonstrated that some tools are comprehensive and mature enough to be used on most annotation projects. The highest score of 0.81 was obtained by WebAnno (of a maximum value of 1.0)., 1477-4054
3. Enberg, Pekka (2024) Latency - Reduce delay in software systems. Manning Publications Co., New York, ISBN 9781633438088, May
4. Diehl, Alexander D. and Meehan, Terrence F. and Bradford, Yvonne M. and Brush, Matthew H. and Dahdul, Wasila M. and Dougall, David S. and He, Yongqun and {Osumi-Sutherland}, David and Ruttenberg, Alan and Sarntivijai, Sirarat and Van Slyke, Ceri E. and Vasilevsky, Nicole A. and Haendel, Melissa A. and Blake, Judith A. and Mungall, Christopher J. (2016) The {{Cell Ontology}} 2016: Enhanced Content, Modularization, and Ontology Interoperability. Journal of Biomedical Semantics 7(1): 44 https://doi.org/10.1186/s13326-016-0088-7, /Users/nishad/Zotero/storage/F7K7MLC5/Diehl et al. - 2016 - The Cell Ontology 2016 enhanced content, modulari.pdf;/Users/nishad/Zotero/storage/7NDBUBUT/s13326-016-0088-7.html, Anatomy Ontology,Cell Line Cell,Gene Ontology,Logical Definition,Neuroscience Information Framework, The Cell Ontology
5. (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies., https://doi.org/10.1186/s13326-016-0088-7, 2041-1480, July, The {{Cell Ontology}} 2016