Example of Biology Direct format
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Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format Example of Biology Direct format
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Biology Direct — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Applied Mathematics #49 of 548 down down by 19 ranks
Agricultural and Biological Sciences (all) #19 of 209 down down by 1 rank
Ecology, Evolution, Behavior and Systematics #79 of 647 up up by 6 ranks
Modeling and Simulation #43 of 290 down down by 24 ranks
Biochemistry, Genetics and Molecular Biology (all) #47 of 204 down down by 5 ranks
Immunology #97 of 202 down down by 7 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 106 Published Papers | 566 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 16/07/2020
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Related Journals

open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 4.9
SJR: 0.657
SNIP: 0.944
open access Open Access
recommended Recommended

EMBO Press

Quality:  
High
CiteRatio: 15.6
SJR: 8.523
SNIP: 2.323

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.

2.193

27% from 2018

Impact factor for Biology Direct from 2016 - 2019
Year Value
2019 2.193
2018 3.01
2017 2.649
2016 2.856
graph view Graph view
table view Table view

5.3

5% from 2019

CiteRatio for Biology Direct from 2016 - 2020
Year Value
2020 5.3
2019 5.6
2018 6.1
2017 5.1
2016 3.9
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 27% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has decreased by 5% 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.

1.515

15% from 2019

SJR for Biology Direct from 2016 - 2020
Year Value
2020 1.515
2019 1.316
2018 1.388
2017 1.694
2016 1.961
graph view Graph view
table view Table view

0.684

1% from 2019

SNIP for Biology Direct from 2016 - 2020
Year Value
2020 0.684
2019 0.679
2018 0.951
2017 0.684
2016 0.793
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 15% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 1% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Biology Direct

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Springer

Biology Direct

Approved by publishing and review experts on SciSpace, this template is built as per for Biology Direct formatting guidelines as mentioned in Springer author instructions. The current version was created on and has been used by 695 authors to write and format their manuscripts to this journal.

i
Last updated on
16 Jul 2020
i
ISSN
1745-6150
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Citation Type
Author Year
(Blonder et al, 1982)
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Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1186/1745-6150-1-7
A putative RNA-interference-based immune system in prokaryotes: computational analysis of the predicted enzymatic machinery, functional analogies with eukaryotic RNAi, and hypothetical mechanisms of action
Kira S. Makarova1, Nick V. Grishin2, Svetlana A. Shabalina1, Yuri I. Wolf1, Eugene V. Koonin1
16 Mar 2006 - Biology Direct

Abstract:

All archaeal and many bacterial genomes contain Clustered Regularly Interspaced Short Palindrome Repeats (CRISPR) and variable arrays of the CRISPR-associated (cas) genes that have been previously implicated in a novel form of DNA repair on the basis of comparative analysis of their protein product sequences. However, the pro... All archaeal and many bacterial genomes contain Clustered Regularly Interspaced Short Palindrome Repeats (CRISPR) and variable arrays of the CRISPR-associated (cas) genes that have been previously implicated in a novel form of DNA repair on the basis of comparative analysis of their protein product sequences. However, the proximity of CRISPR and cas genes strongly suggests that they have related functions which is hard to reconcile with the repair hypothesis. The protein sequences of the numerous cas gene products were classified into ~25 distinct protein families; several new functional and structural predictions are described. Comparative-genomic analysis of CRISPR and cas genes leads to the hypothesis that the CRISPR-Cas system (CASS) is a mechanism of defense against invading phages and plasmids that functions analogously to the eukaryotic RNA interference (RNAi) systems. Specific functional analogies are drawn between several components of CASS and proteins involved in eukaryotic RNAi, including the double-stranded RNA-specific helicase-nuclease (dicer), the endonuclease cleaving target mRNAs (slicer), and the RNA-dependent RNA polymerase. However, none of the CASS components is orthologous to its apparent eukaryotic functional counterpart. It is proposed that unique inserts of CRISPR, some of which are homologous to fragments of bacteriophage and plasmid genes, function as prokaryotic siRNAs (psiRNA), by base-pairing with the target mRNAs and promoting their degradation or translation shutdown. Specific hypothetical schemes are developed for the functioning of the predicted prokaryotic siRNA system and for the formation of new CRISPR units with unique inserts encoding psiRNA conferring immunity to the respective newly encountered phages or plasmids. The unique inserts in CRISPR show virtually no similarity even between closely related bacterial strains which suggests their rapid turnover, on evolutionary scale. Corollaries of this finding are that, even among closely related prokaryotes, the most commonly encountered phages and plasmids are different and/or that the dominant phages and plasmids turn over rapidly. We proposed previously that Cas proteins comprise a novel DNA repair system. The association of the cas genes with CRISPR and, especially, the presence, in CRISPR units, of unique inserts homologous to phage and plasmid genes make us abandon this hypothesis. It appears most likely that CASS is a prokaryotic system of defense against phages and plasmids that functions via the RNAi mechanism. The functioning of this system seems to involve integration of fragments of foreign genes into archaeal and bacterial chromosomes yielding heritable immunity to the respective agents. However, it appears that this inheritance is extremely unstable on the evolutionary scale such that the repertoires of unique psiRNAs are completely replaced even in closely related prokaryotes, presumably, in response to rapidly changing repertoires of dominant phages and plasmids. This article was reviewed by: Eric Bapteste, Patrick Forterre, and Martijn Huynen. Reviewed by Eric Bapteste, Patrick Forterre, and Martijn Huynen. For the full reviews, please go to the Reviewers' comments section. read more read less

Topics:

CRISPR interference (65%)65% related to the paper, CRISPR Loci (65%)65% related to the paper, CRISPR (64%)64% related to the paper, Trans-activating crRNA (61%)61% related to the paper, CRISPR Spacers (58%)58% related to the paper
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1,153 Citations
open accessOpen access Journal Article DOI: 10.1186/1745-6150-7-12
Domain enhanced lookup time accelerated BLAST.
17 Apr 2012 - Biology Direct

Abstract:

Background: BLAST is a commonly-used software package for comparing a query sequence to a database of known sequences; in this study, we focus on protein sequences. Position-specific-iterated BLAST (PSI-BLAST) iteratively searches a protein sequence database, using the matches in round i to construct a position-specific score... Background: BLAST is a commonly-used software package for comparing a query sequence to a database of known sequences; in this study, we focus on protein sequences. Position-specific-iterated BLAST (PSI-BLAST) iteratively searches a protein sequence database, using the matches in round i to construct a position-specific score matrix (PSSM) for searching the database in round i+1. Biegert and Soding developed Context-sensitive BLAST (CS-BLAST), which combines information from searching the sequence database with information derived from a library of short protein profiles to achieve better homology detection than PSI-BLAST, which builds its PSSMs from scratch. Results: We describe a new method, called domain enhanced lookup time accelerated BLAST (DELTA-BLAST), which searches a database of pre-constructed PSSMs before searching a protein-sequence database, to yield better homology detection. For its PSSMs, DELTA-BLAST employs a subset of NCBI’s Conserved Domain Database (CDD). On a test set derived from ASTRAL, with one round of searching, DELTA-BLAST achieves a ROC5000 of 0.270 vs. 0.116 for CS-BLAST. The performance advantage diminishes in iterated searches, but DELTA-BLAST continues to achieve better ROC scores than CS-BLAST. Conclusions: DELTA-BLAST is a useful program for the detection of remote protein homologs. It is available under the “Protein BLAST” link at http://blast.ncbi.nlm.nih.gov. read more read less

Topics:

Sequence database (63%)63% related to the paper, Conserved Domain Database (59%)59% related to the paper
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694 Citations
open accessOpen access Journal Article DOI: 10.1186/1745-6150-1-29
The ancient Virus World and evolution of cells
Eugene V. Koonin1, Tatiana G. Senkevich, Valerian V. Dolja2
19 Sep 2006 - Biology Direct

Abstract:

Recent advances in genomics of viruses and cellular life forms have greatly stimulated interest in the origins and evolution of viruses and, for the first time, offer an opportunity for a data-driven exploration of the deepest roots of viruses. Here we briefly review the current views of virus evolution and propose a new, coh... Recent advances in genomics of viruses and cellular life forms have greatly stimulated interest in the origins and evolution of viruses and, for the first time, offer an opportunity for a data-driven exploration of the deepest roots of viruses. Here we briefly review the current views of virus evolution and propose a new, coherent scenario that appears to be best compatible with comparative-genomic data and is naturally linked to models of cellular evolution that, from independent considerations, seem to be the most parsimonious among the existing ones. Several genes coding for key proteins involved in viral replication and morphogenesis as well as the major capsid protein of icosahedral virions are shared by many groups of RNA and DNA viruses but are missing in cellular life forms. On the basis of this key observation and the data on extensive genetic exchange between diverse viruses, we propose the concept of the ancient virus world. The virus world is construed as a distinct contingent of viral genes that continuously retained its identity throughout the entire history of life. Under this concept, the principal lineages of viruses and related selfish agents emerged from the primordial pool of primitive genetic elements, the ancestors of both cellular and viral genes. Thus, notwithstanding the numerous gene exchanges and acquisitions attributed to later stages of evolution, most, if not all, modern viruses and other selfish agents are inferred to descend from elements that belonged to the primordial genetic pool. In this pool, RNA viruses would evolve first, followed by retroid elements, and DNA viruses. The Virus World concept is predicated on a model of early evolution whereby emergence of substantial genetic diversity antedates the advent of full-fledged cells, allowing for extensive gene mixing at this early stage of evolution. We outline a scenario of the origin of the main classes of viruses in conjunction with a specific model of precellular evolution under which the primordial gene pool dwelled in a network of inorganic compartments. Somewhat paradoxically, under this scenario, we surmise that selfish genetic elements ancestral to viruses evolved prior to typical cells, to become intracellular parasites once bacteria and archaea arrived at the scene. Selection against excessively aggressive parasites that would kill off the host ensembles of genetic elements would lead to early evolution of temperate virus-like agents and primitive defense mechanisms, possibly, based on the RNA interference principle. The emergence of the eukaryotic cell is construed as the second melting pot of virus evolution from which the major groups of eukaryotic viruses originated as a result of extensive recombination of genes from various bacteriophages, archaeal viruses, plasmids, and the evolving eukaryotic genomes. Again, this vision is predicated on a specific model of the emergence of eukaryotic cell under which archaeo-bacterial symbiosis was the starting point of eukaryogenesis, a scenario that appears to be best compatible with the data. The existence of several genes that are central to virus replication and structure, are shared by a broad variety of viruses but are missing from cellular genomes (virus hallmark genes) suggests the model of an ancient virus world, a flow of virus-specific genes that went uninterrupted from the precellular stage of life's evolution to this day. This concept is tightly linked to two key conjectures on evolution of cells: existence of a complex, precellular, compartmentalized but extensively mixing and recombining pool of genes, and origin of the eukaryotic cell by archaeo-bacterial fusion. The virus world concept and these models of major transitions in the evolution of cells provide complementary pieces of an emerging coherent picture of life's history. W. Ford Doolittle, J. Peter Gogarten, and Arcady Mushegian. read more read less

Topics:

Viral evolution (64%)64% related to the paper, Non-cellular life (62%)62% related to the paper, Archaeal Viruses (58%)58% related to the paper, Nucleocytoplasmic large DNA viruses (57%)57% related to the paper, Evolution of cells (54%)54% related to the paper
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629 Citations
open accessOpen access Journal Article DOI: 10.1186/1745-6150-4-14
Transcript length bias in RNA-seq data confounds systems biology
Alicia Oshlack1, Matthew Wakefield1
16 Apr 2009 - Biology Direct

Abstract:

Several recent studies have demonstrated the effectiveness of deep sequencing for transcriptome analysis (RNA-seq) in mammals. As RNA-seq becomes more affordable, whole genome transcriptional profiling is likely to become the platform of choice for species with good genomic sequences. As yet, a rigorous analysis methodology h... Several recent studies have demonstrated the effectiveness of deep sequencing for transcriptome analysis (RNA-seq) in mammals. As RNA-seq becomes more affordable, whole genome transcriptional profiling is likely to become the platform of choice for species with good genomic sequences. As yet, a rigorous analysis methodology has not been developed and we are still in the stages of exploring the features of the data. We investigated the effect of transcript length bias in RNA-seq data using three different published data sets. For standard analyses using aggregated tag counts for each gene, the ability to call differentially expressed genes between samples is strongly associated with the length of the transcript. Transcript length bias for calling differentially expressed genes is a general feature of current protocols for RNA-seq technology. This has implications for the ranking of differentially expressed genes, and in particular may introduce bias in gene set testing for pathway analysis and other multi-gene systems biology analyses. This article was reviewed by Rohan Williams (nominated by Gavin Huttley), Nicole Cloonan (nominated by Mark Ragan) and James Bullard (nominated by Sandrine Dudoit). read more read less
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520 Citations
open accessOpen access Journal Article DOI: 10.1186/1745-6150-6-38
Unification of Cas protein families and a simple scenario for the origin and evolution of CRISPR-Cas systems
Kira S. Makarova1, L. Aravind1, Yuri I. Wolf1, Eugene V. Koonin1
14 Jul 2011 - Biology Direct

Abstract:

The CRISPR-Cas adaptive immunity systems that are present in most Archaea and many Bacteria function by incorporating fragments of alien genomes into specific genomic loci, transcribing the inserts and using the transcripts as guide RNAs to destroy the genome of the cognate virus or plasmid. This RNA interference-like immune ... The CRISPR-Cas adaptive immunity systems that are present in most Archaea and many Bacteria function by incorporating fragments of alien genomes into specific genomic loci, transcribing the inserts and using the transcripts as guide RNAs to destroy the genome of the cognate virus or plasmid. This RNA interference-like immune response is mediated by numerous, diverse and rapidly evolving Cas (CRISPR-associated) proteins, several of which form the Cascade complex involved in the processing of CRISPR transcripts and cleavage of the target DNA. Comparative analysis of the Cas protein sequences and structures led to the classification of the CRISPR-Cas systems into three Types (I, II and III). A detailed comparison of the available sequences and structures of Cas proteins revealed several unnoticed homologous relationships. The Repeat-Associated Mysterious Proteins (RAMPs) containing a distinct form of the RNA Recognition Motif (RRM) domain, which are major components of the CRISPR-Cas systems, were classified into three large groups, Cas5, Cas6 and Cas7. Each of these groups includes many previously uncharacterized proteins now shown to adopt the RAMP structure. Evidence is presented that large subunits contained in most of the CRISPR-Cas systems could be homologous to Cas10 proteins which contain a polymerase-like Palm domain and are predicted to be enzymatically active in Type III CRISPR-Cas systems but inactivated in Type I systems. These findings, the fact that the CRISPR polymerases, RAMPs and Cas2 all contain core RRM domains, and distinct gene arrangements in the three types of CRISPR-Cas systems together provide for a simple scenario for origin and evolution of the CRISPR-Cas machinery. Under this scenario, the CRISPR-Cas system originated in thermophilic Archaea and subsequently spread horizontally among prokaryotes. Because of the extreme diversity of CRISPR-Cas systems, in-depth sequence and structure comparison continue to reveal unexpected homologous relationship among Cas proteins. Unification of Cas protein families previously considered unrelated provides for improvement in the classification of CRISPR-Cas systems and a reconstruction of their evolution. This article was reviewed by Malcolm White (nominated by Purficacion Lopez-Garcia), Frank Eisenhaber and Igor Zhulin. For the full reviews, see the Reviewers' Comments section. read more read less

Topics:

CRISPR (55%)55% related to the paper, Protein family (51%)51% related to the paper
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476 Citations
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Frequently asked questions

1. Can I write Biology Direct in LaTeX?

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

2. Do you follow the Biology Direct guidelines?

Yes, the template is compliant with the Biology Direct 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 Biology Direct?

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 Biology Direct citation style.

4. Can I use the Biology Direct 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 Biology Direct.

5. Can I use a manuscript in Biology Direct 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 Biology Direct that you can download at the end.

6. How long does it usually take you to format my papers in Biology Direct?

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

7. Where can I find the template for the Biology Direct?

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 Biology Direct'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 Biology Direct'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. Biology Direct an online tool or is there a desktop version?

SciSpace's Biology Direct 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 Biology Direct?

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 Biology Direct?”

11. What is the output that I would get after using Biology Direct?

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

12. Is Biology Direct'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 Biology Direct?

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 Biology Direct. 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 Biology Direct?

The 5 most common citation types in order of usage for Biology Direct 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 Biology Direct?

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 Biology Direct's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Biology Direct 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 Biology Direct 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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