Dataset Information

NEMO: Extraction and normalization of organization names from PubMed affiliations.

ABSTRACT: BACKGROUND: Today, there are more than 18 million articles related to biomedical research indexed in MEDLINE, and information derived from them could be used effectively to save the great amount of time and resources spent by government agencies in understanding the scientific landscape, including key opinion leaders and centers of excellence. Associating biomedical articles with organization names could significantly benefit the pharmaceutical marketing industry, health care funding agencies and public health officials and be useful for other scientists in normalizing author names, automatically creating citations, indexing articles and identifying potential resources or collaborators. Large amount of extracted information helps in disambiguating organization names using machine-learning algorithms. RESULTS: We propose NEMO, a system for extracting organization names in the affiliation and normalizing them to a canonical organization name. Our parsing process involves multi-layered rule matching with multiple dictionaries. The system achieves more than 98% f-score in extracting organization names. Our process of normalization that involves clustering based on local sequence alignment metrics and local learning based on finding connected components. A high precision was also observed in normalization. CONCLUSION: NEMO is the missing link in associating each biomedical paper and its authors to an organization name in its canonical form and the Geopolitical location of the organization. This research could potentially help in analyzing large social networks of organizations for landscaping a particular topic, improving performance of author disambiguation, adding weak links in the co-author network of authors, augmenting NLM's MARS system for correcting errors in OCR output of affiliation field, and automatically indexing the PubMed citations with the normalized organization name and country. Our system is available as a graphical user interface available for download along with this paper.

SUBMITTER: Jonnalagadda SR

PROVIDER: S-EPMC2990275 | biostudies-other | 2010

REPOSITORIES: biostudies-other

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NEMO: Extraction and normalization of organization names from PubMed affiliations.

Jonnalagadda Siddhartha Reddy SR Topham Philip P

Journal of biomedical discovery and collaboration 20101004

<h4>Background</h4>Today, there are more than 18 million articles related to biomedical research indexed in MEDLINE, and information derived from them could be used effectively to save the great amount of time and resources spent by government agencies in understanding the scientific landscape, including key opinion leaders and centers of excellence. Associating biomedical articles with organization names could significantly benefit the pharmaceutical marketing industry, health care funding agen ...[more]

PMID: 20922666

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Project description:Podocyte effacement and loss characterizes glomerulopathies such as diabetic nephropathy, lupus, and glomerular toxicity. Human primary podocyte-like epithelial cells cultured from urine (ECU) were characterized as a window to understand podocyte regeneration in these glomerulopathies. Cytokines TNF, and VEGF stimulated regrowth, whereas FGF-1 and IL1 inhibited growth, consistent with other podocyte or parietal epithelial cell models. Review of published micrographs indicated that podocyte foot processes in rodent kidneys interdigitated exclusively with foot processes from other cells, suggesting podocytes practice self-avoidance. In culture, ECU avoided close interactions with other cells arising from the same clone, until enough cells grew for the culture to become confluent. In contrast, ECU derived from multiple clones associated actively to form contiguous monolayers. Gene expression profiling of eight clonal ECU colonies using RNA sequencing revealed that each colony expressed a highly variable profile of the 53 Protocadherin genes. Variable combinations of the 53 Protocadherin PCDHA-, PCDHB-, and PCDHG- gene products are known to act homophilically to direct self-avoidance interactions in human neurons, so PCDH- genes are postulated to govern self-avoidance similarly in podocytes. Such protocadherin profiles could be considered cell names. Transcriptional profiles of ECUs suggest they may represent intermediate stages of Parietal Epithelial Cells (PECs) differentiating into podocytes. They further suggest that each podocyte practices self-avoidance, interdigitating selectively with other cells in the glomerulus. To enable further investigation of multi-clonal podocyte interactions, five podocyte clones were immortalized using temperature-sensitive SV40 Large T antigen. These results suggest that non-self interdigitation of new podocytes with remnant podocytes may facilitate replacement of dying podocytes and re-establishment of a functional filtration barrier.

Dataset Information

NEMO: Extraction and normalization of organization names from PubMed affiliations.

Publications

NEMO: Extraction and normalization of organization names from PubMed affiliations.

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