Example of Journal of Molecular Evolution format
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Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format
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Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format Example of Journal of Molecular Evolution format
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open access Open Access

Journal of Molecular Evolution — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Ecology, Evolution, Behavior and Systematics #200 of 647 down down by 73 ranks
Genetics #189 of 325 down down by 39 ranks
Molecular Biology #275 of 382 down down by 63 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 165 Published Papers | 554 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 22/07/2020
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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.

1.821

2% from 2018

Impact factor for Journal of Molecular Evolution from 2016 - 2019
Year Value
2019 1.821
2018 1.782
2017 1.957
2016 2.434
graph view Graph view
table view Table view

3.4

10% from 2019

CiteRatio for Journal of Molecular Evolution from 2016 - 2020
Year Value
2020 3.4
2019 3.1
2018 3.7
2017 4.1
2016 3.6
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 2% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 10% 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.

0.693

17% from 2019

SJR for Journal of Molecular Evolution from 2016 - 2020
Year Value
2020 0.693
2019 0.591
2018 1.084
2017 0.911
2016 1.182
graph view Graph view
table view Table view

0.61

38% from 2019

SNIP for Journal of Molecular Evolution from 2016 - 2020
Year Value
2020 0.61
2019 0.442
2018 0.476
2017 0.636
2016 0.626
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 17% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 38% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Journal of Molecular Evolution

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Springer

Journal of Molecular Evolution

Journal of Molecular Evolution covers experimental and theoretical work aimed at deciphering features of molecular evolution and the processes bearing on these features, from the initial formation of macromolecular systems onward. Topics addressed in the Journal include the ev...... Read More

Ecology, Evolution, Behavior and Systematics

Genetics

Molecular Biology

Agricultural and Biological Sciences

i
Last updated on
22 Jul 2020
i
ISSN
0022-2844
i
Impact Factor
Medium - 0.562
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
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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

Journal Article DOI: 10.1007/BF01731581
A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences.
Motoo Kimura1

Abstract:

Some simple formulae were obtained which enable us to estimate evolutionary distances in terms of the number of nucleotide substitutions (and, also, the evolutionary rates when the divergence times are known). In comparing a pair of nucleotide sequences, we distinguish two types of differences; if homologous sites are occupie... Some simple formulae were obtained which enable us to estimate evolutionary distances in terms of the number of nucleotide substitutions (and, also, the evolutionary rates when the divergence times are known). In comparing a pair of nucleotide sequences, we distinguish two types of differences; if homologous sites are occupied by different nucleotide bases but both are purines or both pyrimidines, the difference is called type I (or “transition” type), while, if one of the two is a purine and the other is a pyrimidine, the difference is called type II (or “transversion” type). Letting P and Q be respectively the fractions of nucleotide sites showing type I and type II differences between two sequences compared, then the evolutionary distance per site is K = — (1/2) ln {(1 — 2P — Q) }. The evolutionary rate per year is then given by k = K/(2T), where T is the time since the divergence of the two sequences. If only the third codon positions are compared, the synonymous component of the evolutionary base substitutions per site is estimated by K'S = — (1/2) ln (1 — 2P — Q). Also, formulae for standard errors were obtained. Some examples were worked out using reported globin sequences to show that synonymous substitutions occur at much higher rates than amino acid-altering substitutions in evolution. read more read less

Topics:

Ka/Ks ratio (59%)59% related to the paper, Models of DNA evolution (53%)53% related to the paper, Transversion (52%)52% related to the paper, Nonsynonymous substitution (51%)51% related to the paper, Transition (genetics) (50%)50% related to the paper
26,016 Citations
Journal Article DOI: 10.1007/BF01734359
Evolutionary trees from DNA sequences: A maximum likelihood approach
Joseph Felsenstein1

Abstract:

The application of maximum likelihood techniques to the estimation of evolutionary trees from nucleic acid sequence data is discussed. A computationally feasible method for finding such maximum likelihood estimates is developed, and a computer program is available. This method has advantages over the traditional parsimony alg... The application of maximum likelihood techniques to the estimation of evolutionary trees from nucleic acid sequence data is discussed. A computationally feasible method for finding such maximum likelihood estimates is developed, and a computer program is available. This method has advantages over the traditional parsimony algorithms, which can give misleading results if rates of evolution differ in different lineages. It also allows the testing of hypotheses about the constancy of evolutionary rates by likelihood ratio tests, and gives rough indication of the error of the estimate of the tree. read more read less

Topics:

Tree rearrangement (65%)65% related to the paper, Maximum likelihood sequence estimation (63%)63% related to the paper, Expectation–maximization algorithm (60%)60% related to the paper, Computational phylogenetics (59%)59% related to the paper, Ancestral reconstruction (57%)57% related to the paper
13,111 Citations
Journal Article DOI: 10.1007/BF02101694
Dating of the human-ape splitting by a molecular clock of mitochondrial DNA.
Masami Hasegawa, Hirohisa Kishino, Taka-aki Yano1

Abstract:

A new statistical method for estimating divergence dates of species from DNA sequence data by a molecular clock approach is developed. This method takes into account effectively the information contained in a set of DNA sequence data. The molecular clock of mitochondrial DNA (mtDNA) was calibrated by setting the date of diver... A new statistical method for estimating divergence dates of species from DNA sequence data by a molecular clock approach is developed. This method takes into account effectively the information contained in a set of DNA sequence data. The molecular clock of mitochondrial DNA (mtDNA) was calibrated by setting the date of divergence between primates and ungulates at the Cretaceous-Tertiary boundary (65 million years ago), when the extinction of dinosaurs occurred. A generalized least-squares method was applied in fitting a model to mtDNA sequence data, and the clock gave dates of 92.3 +/- 11.7, 13.3 +/- 1.5, 10.9 +/- 1.2, 3.7 +/- 0.6, and 2.7 +/- 0.6 million years ago (where the second of each pair of numbers is the standard deviation) for the separation of mouse, gibbon, orangutan, gorilla, and chimpanzee, respectively, from the line leading to humans. Although there is some uncertainty in the clock, this dating may pose a problem for the widely believed hypothesis that the pipedal creature Australopithecus afarensis, which lived some 3.7 million years ago at Laetoli in Tanzania and at Hadar in Ethiopia, was ancestral to man and evolved after the human-ape splitting. Another likelier possibility is that mtDNA was transferred through hybridization between a proto-human and a proto-chimpanzee after the former had developed bipedalism. read more read less

Topics:

Molecular clock (56%)56% related to the paper, Australopithecus afarensis (52%)52% related to the paper
8,124 Citations
Journal Article DOI: 10.1007/BF02100115
Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea

Abstract:

A maximum likelihood method for inferring evolutionary trees from DNA sequence data was developed by Felsenstein (1981). In evaluating the extent to which the maximum likelihood tree is a significantly better representation of the true tree, it is important to estimate the variance of the difference between log likelihood of ... A maximum likelihood method for inferring evolutionary trees from DNA sequence data was developed by Felsenstein (1981). In evaluating the extent to which the maximum likelihood tree is a significantly better representation of the true tree, it is important to estimate the variance of the difference between log likelihood of different tree topologies. Bootstrap resampling can be used for this purpose (Hasegawa et al. 1988; Hasegawa and Kishino 1989), but it imposes a great computation burden. To overcome this difficulty, we developed a new method for estimating the variance by expressing it explicitly. The method was applied to DNA sequence data from primates in order to evaluate the maximum likelihood branching order among Hominoidea. It was shown that, although the orangutan is convincingly placed as an outgroup of a human and African apes clade, the branching order among human, chimpanzee, and gorilla cannot be determined confidently from the DNA sequence data presently available when the evolutionary rate constancy is not assumed. read more read less

Topics:

Tree rearrangement (60%)60% related to the paper, Maximum likelihood sequence estimation (57%)57% related to the paper, Phylogenetic tree (55%)55% related to the paper
3,157 Citations
open accessOpen access Journal Article DOI: 10.1007/BF00160154
Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods
Ziheng Yang1

Abstract:

Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called the "discrete gamma model," uses... Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called the "discrete gamma model," uses several categories of rates to approximate the gamma distribution, with equal probability for each category. The mean of each category is used to represent all the rates falling in the category. The performance of this method is found to be quite good, and four such categories appear to be sufficient to produce both an optimum, or near-optimum fit by the model to the data, and also an acceptable approximation to the continuous distribution. The second method, called "fixed-rates model", classifies sites into several classes according to their rates predicted assuming the star tree. Sites in different classes are then assumed to be evolving at these fixed rates when other tree topologies are evaluated. Analyses of the data sets suggest that this method can produce reasonable results, but it seems to share some properties of a least-squares pairwise comparison; for example, interior branch lengths in nonbest trees are often found to be zero. The computational requirements of the two methods are comparable to that of Felsenstein's (1981, J Mol Evol 17:368-376) model, which assumes a single rate for all the sites. read more read less

Topics:

Covarion (53%)53% related to the paper, Substitution model (53%)53% related to the paper, Gamma distribution (52%)52% related to the paper
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2,718 Citations
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Frequently asked questions

1. Can I write Journal of Molecular Evolution in LaTeX?

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

2. Do you follow the Journal of Molecular Evolution guidelines?

Yes, the template is compliant with the Journal of Molecular Evolution 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 Journal of Molecular Evolution?

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 Journal of Molecular Evolution citation style.

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After writing your paper autoformatting in Journal of Molecular Evolution, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Journal of Molecular Evolution'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 Journal of Molecular Evolution?

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 Journal of Molecular Evolution. 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 Journal of Molecular Evolution?

The 5 most common citation types in order of usage for Journal of Molecular Evolution are:.

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

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16. Can I download Journal of Molecular Evolution 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 Journal of Molecular Evolution Endnote style according to Elsevier guidelines.

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