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Related Concept Videos

Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Next-generation Sequencing03:00

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Although all next-generation methods use different technologies, they all share a set of standard features.

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Related Experiment Video

Updated: Jun 25, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

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

Published on: October 24, 2019

Sequential result refinement for searching the biomedical literature.

L Y Tanaka1, J R Herskovic, M S Iyengar

  • 1School of Health Information Sciences, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, TX 77030, USA. lent@hawaii.edu

Journal of Biomedical Informatics
|March 11, 2009
PubMed
Summary

This study introduces a new method to identify highly cited biomedical articles from MEDLINE, addressing information overload. The approach uses Medical Subject Headings, journal impact factor, and author count to filter results effectively.

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

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Last Updated: Jun 25, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
05:02

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

Published on: October 24, 2019

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
09:34

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

  • Biomedical Informatics
  • Information Retrieval
  • Bibliometrics

Background:

  • Information overload is a significant challenge for users of the MEDLINE database, which contains over 17 million biomedical articles.
  • Current methods for identifying important articles, such as citation counts, have limitations including proprietary data, cost, and citation lag.

Purpose of the Study:

  • To develop and evaluate a novel method for predicting highly cited articles using readily available information at the time of MEDLINE listing.
  • To assist users who prioritize precision over recall by filtering large result sets to identify a smaller number of high-quality articles.

Main Methods:

  • A scoring system was developed incorporating Medical Subject Headings (MeSH) terms, Journal Impact Factor (JIF), and the number of authors.
  • The method was evaluated for its ability to filter large MEDLINE result sets (>1000 articles) generated by user queries.

Main Results:

  • The proposed method successfully identifies articles likely to be highly cited.
  • The scoring system effectively filters extensive MEDLINE results into smaller, more relevant sets.

Conclusions:

  • This method offers a practical solution for users seeking high-precision retrieval of important biomedical literature from MEDLINE.
  • Utilizing MeSH terms, JIF, and author count provides a viable alternative to citation-based importance metrics, overcoming their inherent limitations.