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Analysis of institutional authors

Larranaga, PedroAuthor

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June 9, 2019
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A review of feature selection techniques in bioinformatics

Publicated to: BIOINFORMATICS. 23 (19): 2507-2517 - 2007-10-01 23(19), DOI: 10.1093/bioinformatics/btm344

Authors:

Saeys, Y; Inza, I; Larrañaga, P
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Affiliations

- Author

Abstract

Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques. In this article, we make the interested reader aware of the possibilities of feature selection, providing a basic taxonomy of feature selection techniques, and discussing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications.
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Keywords

Bayesian variable selectionFalse discovery rateFeature subset-selectionGene-expression dataMass-spectrometry dataMicroarray dataOvarian-cancer identificationSample classificationSplice-site predictionSupport vector machines

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal BIOINFORMATICS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2007, it was in position 8/60, thus managing to position itself as a Q1 (Primer Cuartil), in the category Biochemical Research Methods.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-27:

  • Google Scholar: 5962
  • WoS: 3460
  • Scopus: 4285
  • Europe PMC: 776
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-27:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 4104.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 4094 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 40.
  • The number of mentions on the social network X (formerly Twitter): 5 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/73113/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 283
  • Downloads: 855
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Belgium.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: Last Author (LARRAÑAGA MUGICA, PEDRO MARIA).

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