Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pleiotropy

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...

Cancer

Cancer

Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.

Pedigree Analysis

Pedigree Analysis

Life Histories

Life Histories

Sex-linked Disorders

Sex-linked Disorders

Like autosomes, sex chromosomes contain a variety of genes necessary for normal body function. When a mutation in one of these genes results in biological deficits, the disorder is considered sex-linked.

Symbiosis

Symbiosis

Symbiotic relationships are long-term, close interactions between individuals of different species that affect the distribution and abundance of those species. When a relationship is beneficial to both species, this is called mutualism. When the relationship is beneficial to one species but neither beneficial nor harmful to the other species, this is called commensalism. When one organism is harmed to benefit another, the relationship is known as parasitism. These types of relationships often...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Improving hit discovery by integrating activity cliff sensitivity into active learning.

Bioinformatics (Oxford, England)·2026

Same author

MedHopQA: A Disease-Centered Multi-Hop Reasoning Benchmark and Evaluation Framework for LLM-Based Biomedical Question Answering.

ArXiv·2026

Same author

Exploring Anti-Aging Literature via <i>ConvexTopics</i> and Large Language Models.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026

Same author

Validation of a 2-Gene Blood Test for Kawasaki Disease in Febrile Children.

JAMA network open·2026

Same author

Deep learning for predicting patient drug response by transferring gene-level and cell-level knowledge to tumors.

NPJ precision oncology·2026

Same author

Exploring Anti-Aging Literature via <i>ConvexTopics</i> and Large Language Models.

ArXiv·2026

Search research articles

Related Experiment Video

Updated: Feb 25, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Author Name Disambiguation for PubMed.

Wanli Liu¹, Rezarta Islamaj Doğan¹, Sun Kim¹

¹National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda MD, 20894.

Journal of the Association for Information Science and Technology

|August 1, 2017

Summary

PubMed searches using author names are improved by a new disambiguation system. This system reduces errors in author name clustering, enhancing literature retrieval accuracy and user experience.

More Related Videos

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Related Experiment Videos

Last Updated: Feb 25, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Area of Science:

Bibliometrics
Information Retrieval
Computational Linguistics

Background:

PubMed users frequently search scientific literature using author names.
Author name ambiguity in queries leads to irrelevant search results and a poor user experience.
Existing systems struggle to accurately disambiguate authors with similar names.

Purpose of the Study:

To design and evaluate an author name disambiguation system for PubMed.
To improve the accuracy of clustering scientific papers by the same author.
To enhance the user experience for author-based literature searches in PubMed.

Main Methods:

Developed an author name disambiguation system using similarity estimation and agglomerative clustering.
Employed a machine-learning method to score features for disambiguating author name pairs.
Utilized a clustering algorithm regulated by name compatibility and probability, with transitivity violation correction.

Main Results:

The new system achieved a 2.2% lumping error rate and a 7.7% splitting error rate, with an overall error rate of 9.9%.
This represents a significant improvement over the state-of-the-art system's overall error rate of 11.9%.
Integration into PubMed improved the click-through rate for author name queries from 34.9% to 36.9%.

Conclusions:

The developed author name disambiguation system effectively reduces clustering errors.
The machine-learning approach and precision-focused clustering algorithm contribute to improved accuracy.
The system enhances PubMed's search functionality, leading to better literature retrieval and user satisfaction.