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Briefings in Functional Genomics
H-index 16

Briefings in Functional Genomics

2041-2649

Published by: Oxford University Press

https://academic.oup.com/bfg

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Genetics 126 7 7 6
Biology and Biochemistry 733 16 14 6

Additional Metrics

Number of Best Scientists*: 53
Documents by Best Scientists*: 62
Top 100 Ranked Scientists*: 1
SCIMAGO H-index: 87
SCIMAGO SJR: 0.86
Impact Factor: 2.5

Overview

Top Research Topics at Briefings in Functional Genomics?

Briefings in Functional Genomics investigates studies in Computational biology, Genetics, Genome, Gene and Genomics. While Computational biology is the focus of Briefings in Functional Genomics, it also provided insights into the studies of Bioinformatics, RNA, Identification (biology), Functional genomics and DNA sequencing. The Genetics research presented places emphasis on topics like Epigenetics, Regulation of gene expression, Gene expression, Phenotype and Epigenomics.

The studies on Epigenetics discussed can also contribute to research in the domains of Chromatin, Histone, DNA methylation and Cell biology. Briefings in Functional Genomics focused on Regulation of gene expression research but expanded to cover Transcription factor. Briefings in Functional Genomics facilitates discussions on Genome that incorporate concepts from other fields like Evolutionary biology and Gene regulatory network.

The Gene study tackled is a key component of adjacent topics in the area of Function (biology).

  • Computational biology (46.25%)
  • Genetics (35.95%)
  • Genome (22.51%)

What are the most cited papers published in the journal?

  • Genomic selection in plant breeding: from theory to practice. (763 citations)
  • RADSeq: next-generation population genetics (479 citations)
  • The IL-10/STAT3-mediated anti-inflammatory response: recent developments and future challenges (211 citations)

Research areas of the most cited articles at Briefings in Functional Genomics:

The journal papers mostly deal with topics like Computational biology, Genetics, Genome, DNA sequencing and Genomics. In addition to Computational biology research, the journal papers aim to explore topics under Transcriptome, Gene expression, Biotechnology, Proteomics and Chromatin. Most of the Genetics studies addressed in the most cited articles also intersect with Evolutionary biology.

What topics the last edition of the journal is best known for?

  • Gene
  • DNA
  • Genome

The previous edition focused in particular on these issues:

The journal mostly deals with topics like Computational biology, Gene, RNA, Cell biology and Zebrafish. Topics in Computational biology were tackled in line with various other fields like Cancer, Non-coding RNA, CRISPR, Identification (biology) and Function (biology). While work presented in the journal provided substantial information on Gene, it also covered topics in Biotechnology research, State (computer science) and Cluster analysis.

The concepts on RNA presented in Briefings in Functional Genomics can also apply to other research fields, including RNA methylation, Ribosomal RNA, Transcriptome, DNA and Messenger RNA. Topics in Zebrafish explored in the journal were investigated in conjunction with research in Chromosome, Cohesin, Model organism and Genomics. Briefings in Functional Genomics focuses on Human genome research as part of the broader topic of Genetics.

The most cited articles from the last journal are:

  • Critical evaluation of web-based DNA N6-methyladenine site prediction tools (6 citations)
  • A comprehensive review for gut microbes: technologies, interventions, metabolites and diseases. (5 citations)
  • Prediction of bio-sequence modifications and the associations with diseases. (5 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Briefings in Functional Genomics (based on the number of publications) are:

  • Quan Zou (12 papers) published 5 papers at the last edition, 3 more than at the previous edition,
  • David Roy Smith (5 papers) absent at the last edition,
  • Min Zhao (4 papers) published 1 paper at the last edition,
  • Subhadip Basu (4 papers) absent at the last edition,
  • An-Liang Xia (3 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Briefings in Functional Genomics (based on the number of publications) are:

  • University of Cambridge (15 papers) absent at the last edition,
  • Max Planck Society (10 papers) published 2 papers at the last edition,
  • Xuzhou Medical College (9 papers) absent at the last edition,
  • Wellcome Trust Sanger Institute (8 papers) absent at the last edition,
  • University of Oxford (8 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 34.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 15.15% were posted by at least one author from the top 10 institutions publishing in the journal. Another 15.15% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.21% of all publications and 48.48% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • Review of multi-omics data resources and integrative analysis for human brain disorders.

    Xianjun Dong;Chunyu Liu;Mikhail Dozmorov

    (2021)
    26 Citations
  • The impact of epitranscriptomic marks on post-transcriptional regulation in plants.

    Xiang Yu;Bishwas Sharma;Brian D Gregory

    (2021)
    22 Citations
  • Strandedness during cDNA synthesis, the stranded parameter in htseq-count and analysis of RNA-Seq data.

    Krishna A Srinivasan;Suman K Virdee;Andrew G McArthur

    (2020)
    17 Citations
  • CRISPR/Cas9 technology: towards a new generation of improved CAR-T cells for anticancer therapies.

    Guillermo Ureña-Bailén;Andrés Lamsfus-Calle;Alberto Daniel-Moreno;Janani Raju

    (2020)
    16 Citations
  • Molecular language models: RNNs or transformer?

    (2023)
    14 Citations
  • ‘Green revolution’ dwarf gene sd1 of rice has gigantic impact

    Vikram Singh Gaur;Giresh Channappa;Mridul Chakraborti;Tilak Raj Sharma

    (2020)
    14 Citations
  • Application of omics research in seaweeds with a focus on red seaweeds.

    Zubaida P Patwary;Nicholas A Paul;Koki Nishitsuji;Alexandra H Campbell

    (2021)
    14 Citations
  • Single-cell transcriptomics allows novel insights into aging and circadian processes.

    Sara S Fonseca Costa;Sara S Fonseca Costa;Marc Robinson-Rechavi;Marc Robinson-Rechavi;Jürgen A Ripperger

    (2020)
    10 Citations
  • Functional long non-coding and circular RNAs in zebrafish

    Gyan Ranjan;Paras Sehgal;Disha Sharma;Vinod Scaria

    (2021)
    9 Citations
  • Computational resources for identification of cancer biomarkers from omics data.

    Harpreet Kaur;Rajesh Kumar;Anjali Lathwal;Gajendra P S Raghava

    (2021)
    9 Citations

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