Mining the Proteome Associated with Rheumatic and Autoimmune Diseases. Ruiz-Romero, C., Lam, M. P. Y., Nilsson, P., Önnerfjord, P., Utz, P. J., Van Eyk, J. E., Venkatraman, V., Fert-Bober, J., Watt, F. E., & Blanco, F. J. Journal of proteome research, 18(12):4231–4239, December, 2019. Place: United States
doi  abstract   bibtex   
A steady increase in the incidence of osteoarthritis and other rheumatic diseases has been observed in recent decades, including autoimmune conditions such as rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are characterized by the inflammation of joints, muscles, or other connective tissues. In addition to often experiencing debilitating mobility and pain, RAD patients are also at a higher risk of suffering comorbidities such as cardiovascular or infectious events. Given the socioeconomic impact of RADs, broad research efforts have been dedicated to these diseases worldwide. In the present work, we applied literature mining platforms to identify "popular" proteins closely related to RADs. The platform is based on publicly available literature. The results not only will enable the systematic prioritization of candidates to perform targeted proteomics studies but also may lead to a greater insight into the key pathogenic processes of these disorders.
@article{ruiz-romero_mining_2019,
	title = {Mining the {Proteome} {Associated} with {Rheumatic} and {Autoimmune} {Diseases}.},
	volume = {18},
	issn = {1535-3907 1535-3893},
	doi = {10.1021/acs.jproteome.9b00360},
	abstract = {A steady increase in the incidence of osteoarthritis and other rheumatic diseases  has been observed in recent decades, including autoimmune conditions such as  rheumatoid arthritis, spondyloarthropathies, systemic lupus erythematosus, systemic  sclerosis, and Sjögren's syndrome. Rheumatic and autoimmune diseases (RADs) are  characterized by the inflammation of joints, muscles, or other connective tissues.  In addition to often experiencing debilitating mobility and pain, RAD patients are  also at a higher risk of suffering comorbidities such as cardiovascular or  infectious events. Given the socioeconomic impact of RADs, broad research efforts  have been dedicated to these diseases worldwide. In the present work, we applied  literature mining platforms to identify "popular" proteins closely related to RADs.  The platform is based on publicly available literature. The results not only will  enable the systematic prioritization of candidates to perform targeted proteomics  studies but also may lead to a greater insight into the key pathogenic processes of  these disorders.},
	language = {eng},
	number = {12},
	journal = {Journal of proteome research},
	author = {Ruiz-Romero, Cristina and Lam, Maggie P. Y. and Nilsson, Peter and Önnerfjord, Patrik and Utz, Paul J. and Van Eyk, Jennifer E. and Venkatraman, Vidya and Fert-Bober, Justyna and Watt, Fiona E. and Blanco, Francisco J.},
	month = dec,
	year = {2019},
	pmid = {31599600},
	note = {Place: United States},
	keywords = {*Human Proteome Project, *Proteome, *autoimmune diseases, *bioinformatics, *osteoarthritis, *rheumatic diseases, Arthritis, Rheumatoid/metabolism, Autoimmune Diseases/*metabolism, Data Mining, Humans, Osteoarthritis/metabolism, Proteins/*metabolism, Rheumatic Diseases/*metabolism},
	pages = {4231--4239}
}

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