Example of Current Bioinformatics format
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Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format
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Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format Example of Current Bioinformatics format
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open access Open Access

Current Bioinformatics — Template for authors

Publisher: Bentham Science
Categories Rank Trend in last 3 yrs
Computational Mathematics #67 of 152 up up by 28 ranks
Genetics #221 of 325 up up by 52 ranks
Biochemistry #292 of 415 up up by 55 ranks
Molecular Biology #302 of 382 up up by 41 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 300 Published Papers | 808 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 08/06/2020
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Related Journals

open access Open Access
recommended Recommended

Oxford University Press

Quality:  
High
CiteRatio: 9.9
SJR: 3.599
SNIP: 2.056
open access Open Access
recommended Recommended

EMBO Press

Quality:  
High
CiteRatio: 10.6
SJR: 4.584
SNIP: 1.577
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 7.0
SJR: 1.329
SNIP: 1.627
open access Open Access

Wiley

Quality:  
High
CiteRatio: 8.5
SJR: 2.677
SNIP: 1.204

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

2.068

74% from 2018

Impact factor for Current Bioinformatics from 2016 - 2019
Year Value
2019 2.068
2018 1.189
2017 0.54
2016 0.6
graph view Graph view
table view Table view

2.7

29% from 2019

CiteRatio for Current Bioinformatics from 2016 - 2020
Year Value
2020 2.7
2019 2.1
2018 1.2
2017 1.2
2016 1.3
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 74% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 29% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.306

8% from 2019

SJR for Current Bioinformatics from 2016 - 2020
Year Value
2020 0.306
2019 0.333
2018 0.234
2017 0.251
2016 0.236
graph view Graph view
table view Table view

0.383

32% from 2019

SNIP for Current Bioinformatics from 2016 - 2020
Year Value
2020 0.383
2019 0.29
2018 0.205
2017 0.314
2016 0.301
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 8% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 32% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Current Bioinformatics

Guideline source: View

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Bentham Science

Current Bioinformatics

Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth reviews, drug clinical trial studies and guest edited thematic issues written by leaders in the field, covering a wide range o...... Read More

Mathematics

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Last updated on
07 Jun 2020
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ISSN
1574-8936
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Acceptance Rate
Not provided
i
Frequency
Not provided
i
Open Access
Yes
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Sherpa RoMEO Archiving Policy
Yellow faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
Vancouver
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Citation Type
Numbered
[25]
i
Bibliography Example
Blonder, G E, Tinkham, M, & Klapwijk, T M. Transition from metallic to tunnel- ing regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B. 2013;87(10):100510.

Top papers written in this journal

Journal Article DOI: 10.2174/157489310794072508
A Review of Ensemble Methods in Bioinformatics
Pengyi Yang1, Yee Hwa Yang, Bing Bing Zhou, Albert Y. Zomaya
30 Nov 2010 - Current Bioinformatics

Abstract:

Ensemble learning is an intensively studies technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complexity data structures. The aim of this ... Ensemble learning is an intensively studies technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complexity data structures. The aim of this article is two-fold. First, it is to provide a review of the most widely used ensemble learning methods and their application in various bioinformatics problems, including the main topics of gene expression, mass spectrometry-based proteomics, gene-gene interaction identification from genome-wide association studies, and prediction of regulatory elements from DNA and protein sequences. Second, we try to identify and summarize future trends of ensemble methods in bioinformatics. Promising directions such as ensemble of support vector machine, meta-ensemble, and ensemble based feature selection are discussed. read more read less

Topics:

Ensemble learning (73%)73% related to the paper, Feature selection (52%)52% related to the paper
436 Citations
open accessOpen access Journal Article DOI: 10.2174/157489312799304431
Bioinformatics Tools for Mass Spectroscopy-Based Metabolomic Data Processing and Analysis.
Masahiro Sugimoto1, Masato Kawakami1, Martin Robert1, Tomoyoshi Soga, Masaru Tomita
29 Feb 2012 - Current Bioinformatics

Abstract:

Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, ... Biological systems are increasingly being studied in a holistic manner, using omics approaches, to provide quantitative and qualitative descriptions of the diverse collection of cellular components. Among the omics approaches, metabolomics, which deals with the quantitative global profiling of small molecules or metabolites, is being used extensively to explore the dynamic response of living systems, such as organelles, cells, tissues, organs and whole organisms, under diverse physiological and pathological conditions. This technology is now used routinely in a number of applications, including basic and clinical research, agriculture, microbiology, food science, nutrition, pharmaceutical research, environmental science and the development of biofuels. Of the multiple analytical platforms available to perform such analyses, nuclear magnetic resonance and mass spectrometry have come to dominate, owing to the high resolution and large datasets that can be generated with these techniques. The large multidimensional datasets that result from such studies must be processed and analyzed to render this data meaningful. Thus, bioinformatics tools are essential for the efficient processing of huge datasets, the characterization of the detected signals, and to align multiple datasets and their features. This paper provides a state-of-the-art overview of the data processing tools available, and reviews a collection of recent reports on the topic. Data conversion, pre-processing, alignment, normalization and statistical analysis are introduced, with their advantages and disadvantages, and comparisons are made to guide the reader. read more read less
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285 Citations
Journal Article DOI: 10.2174/157489309787158198
Molecular Genetic Markers: Discovery, Applications, Data Storage and Visualisation
Chris Duran, Nikki Appleby, David Edwards1, Jacqueline Batley
01 Jan 2009 - Current Bioinformatics

Abstract:

Molecular genetic markers represent one of the most powerful tools for the analysis of genomes and enable the association of heritable traits with underlying genomic variation. Molecular marker technology has developed rapidly over the last decade and two forms of sequence based marker, Simple Sequence Repeats (SSRs), also kn... Molecular genetic markers represent one of the most powerful tools for the analysis of genomes and enable the association of heritable traits with underlying genomic variation. Molecular marker technology has developed rapidly over the last decade and two forms of sequence based marker, Simple Sequence Repeats (SSRs), also known as microsatellites, and Single Nucleotide Polymorphisms (SNPs) now predominate applications in modern genetic analysis. The reducing cost of DNA sequencing has led to the availability of large sequence data sets derived from whole genome sequencing and large scale Expressed Sequence Tag (EST) discovery that enable the mining of SSRs and SNPs, which may then be applied to diversity analysis, genetic trait mapping, association studies, and marker assisted selection. These markers are inexpensive, require minimal labour to produce and can frequently be associated with annotated genes. Here we review automated methods for the discovery of SSRs and SNPs and provide an overview of the diverse applications of these markers. read more read less

Topics:

Molecular marker (56%)56% related to the paper, Genetic marker (55%)55% related to the paper, Whole genome sequencing (53%)53% related to the paper, Expressed sequence tag (53%)53% related to the paper, DNA sequencing (52%)52% related to the paper
151 Citations
Journal Article DOI: 10.2174/157489307779314348
Hidden Markov Models in Bioinformatics
01 Jan 2007 - Current Bioinformatics

Abstract:

Hidden Markov Models (HMMs) became recently important and popular among bioinformatics researchers, and many software tools are based on them. In this survey, we first consider in some detail the mathematical foundations of HMMs, we describe the most important algorithms, and provide useful comparisons, pointing out advantage... Hidden Markov Models (HMMs) became recently important and popular among bioinformatics researchers, and many software tools are based on them. In this survey, we first consider in some detail the mathematical foundations of HMMs, we describe the most important algorithms, and provide useful comparisons, pointing out advantages and drawbacks. We then consider the major bioinformatics applications, such as alignment, labeling, and profiling of sequences, protein structure prediction, and pattern recognition. We finally provide a critical appraisal of the use and perspectives of HMMs in bioinformatics. read more read less

Topics:

Hidden Markov model (58%)58% related to the paper, Pattern recognition (psychology) (53%)53% related to the paper, Protein structure prediction (51%)51% related to the paper
View PDF
146 Citations
Journal Article DOI: 10.2174/157489306775330615
Gene Expression Profile Classification: A Review
01 Jan 2006 - Current Bioinformatics

Abstract:

In this review, we have discussed the class-prediction and discovery methods that are applied to gene expression data, along with the implications of the findings. We attempted to present a unified approach that considers both class-prediction and class-discovery. We devoted a substantial part of this review to an overview of... In this review, we have discussed the class-prediction and discovery methods that are applied to gene expression data, along with the implications of the findings. We attempted to present a unified approach that considers both class-prediction and class-discovery. We devoted a substantial part of this review to an overview of pattern classification/recognition methods and discussed important issues such as preprocessing of gene expression data, curse of dimensionality, feature extraction/selection, and measuring or estimating classifier performance. We discussed and summarized important properties such as generalizability (sensitivity to overtraining), built-in feature selection, ability to report prediction strength, and transparency (ease of understanding of the operation) of different class-predictor design approaches to provide a quick and concise reference. We have also covered the topic of biclustering, which is an emerging clustering method that processes the entries of the gene expression data matrix in both gene and sample directions simultaneously, in detail. read more read less

Topics:

Biclustering (56%)56% related to the paper, Feature selection (52%)52% related to the paper, Feature extraction (52%)52% related to the paper, Cluster analysis (51%)51% related to the paper
138 Citations
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SciSpace is a very innovative solution to the formatting problem and existing providers, such as Mendeley or Word did not really evolve in recent years.

- Andreas Frutiger, Researcher, ETH Zurich, Institute for Biomedical Engineering

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With SciSpace, you do not need a word template for Current Bioinformatics.

It automatically formats your research paper to Bentham Science formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Time taken to format a paper and Compliance with guidelines

Plagiarism Reports via Turnitin

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Using this service, researchers can compare submissions against more than 170 million scholarly articles, a database of 70+ billion current and archived web pages. How Turnitin Integration works?

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Current Bioinformatics format uses Vancouver citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. Can I write Current Bioinformatics in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Current Bioinformatics guidelines and auto format it.

2. Do you follow the Current Bioinformatics guidelines?

Yes, the template is compliant with the Current Bioinformatics guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Current Bioinformatics?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Current Bioinformatics citation style.

4. Can I use the Current Bioinformatics templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Current Bioinformatics.

5. Can I use a manuscript in Current Bioinformatics that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Current Bioinformatics that you can download at the end.

6. How long does it usually take you to format my papers in Current Bioinformatics?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Current Bioinformatics.

7. Where can I find the template for the Current Bioinformatics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Current Bioinformatics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Current Bioinformatics's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Current Bioinformatics an online tool or is there a desktop version?

SciSpace's Current Bioinformatics is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Current Bioinformatics?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Current Bioinformatics?”

11. What is the output that I would get after using Current Bioinformatics?

After writing your paper autoformatting in Current Bioinformatics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Current Bioinformatics's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Current Bioinformatics?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Current Bioinformatics. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Current Bioinformatics?

The 5 most common citation types in order of usage for Current Bioinformatics are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Current Bioinformatics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Current Bioinformatics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Current Bioinformatics in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Current Bioinformatics Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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