Example of Genome Medicine format
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Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format
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Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format Example of Genome Medicine format
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open access Open Access ISSN: 1756994X
recommended Recommended

Genome Medicine — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Genetics (clinical) #4 of 87 up up by 3 ranks
Genetics #15 of 325 up up by 11 ranks
Molecular Medicine #10 of 167 up up by 4 ranks
Molecular Biology #27 of 382 up up by 12 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 365 Published Papers | 5546 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 08/06/2020
Insights & related journals
General info
Top papers
Popular templates
Get started guide
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FAQ

Journal Performance & Insights

  • Impact Factor
  • CiteRatio
  • SJR
  • SNIP

Impact factor 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.

10.675

2% from 2018

Impact factor for Genome Medicine from 2016 - 2019
Year Value
2019 10.675
2018 10.886
2017 8.898
2016 7.071
graph view Graph view
table view Table view

insights Insights

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

CiteRatio is a measure of average citations received per peer-reviewed paper published in the journal.

15.2

17% from 2019

CiteRatio for Genome Medicine from 2016 - 2020
Year Value
2020 15.2
2019 18.4
2018 14.5
2017 10.9
2016 8.8
graph view Graph view
table view Table view

insights Insights

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

SCImago Journal Rank (SJR) measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

5.564

13% from 2019

SJR for Genome Medicine from 2016 - 2020
Year Value
2020 5.564
2019 6.411
2018 5.084
2017 4.537
2016 3.966
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 13% in last years.
  • This journal’s SJR is in the top 10 percentile category.

Source Normalized Impact per Paper (SNIP) measures actual citations received relative to citations expected for the journal's category.

2.245

4% from 2019

SNIP for Genome Medicine from 2016 - 2020
Year Value
2020 2.245
2019 2.348
2018 1.909
2017 1.485
2016 1.332
graph view Graph view
table view Table view

insights Insights

  • SNIP of this journal has decreased by 4% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Related Journals

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CiteRatio: 4.7 | SJR: 0.704 | SNIP: 0.589
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PLOS

CiteRatio: 9.0 | SJR: 3.587 | SNIP: 1.457
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CiteRatio: 4.6 | SJR: 1.028 | SNIP: 1.006

Genome Medicine

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Springer

Genome Medicine

Approved by publishing and review experts on SciSpace, this template is built as per for Genome Medicine formatting guidelines as mentioned in Springer author instructions. The current version was created on and has been used by 126 authors to write and format their manuscripts to this journal.

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Last updated on
08 Jun 2020
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ISSN
1606-8610
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Open Access
Yes
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Sherpa RoMEO Archiving Policy
White faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder, G.E., Tinkham, M., Klapwijk, T.M.: Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B 25(7), 4515–4532 (1982)

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1186/S13073-017-0424-2
Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
19 Apr 2017 - Genome Medicine

Abstract:

High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subs... High tumor mutational burden (TMB) is an emerging biomarker of sensitivity to immune checkpoint inhibitors and has been shown to be more significantly associated with response to PD-1 and PD-L1 blockade immunotherapy than PD-1 or PD-L1 expression, as measured by immunohistochemistry (IHC). The distribution of TMB and the subset of patients with high TMB has not been well characterized in the majority of cancer types. In this study, we compare TMB measured by a targeted comprehensive genomic profiling (CGP) assay to TMB measured by exome sequencing and simulate the expected variance in TMB when sequencing less than the whole exome. We then describe the distribution of TMB across a diverse cohort of 100,000 cancer cases and test for association between somatic alterations and TMB in over 100 tumor types. We demonstrate that measurements of TMB from comprehensive genomic profiling are strongly reflective of measurements from whole exome sequencing and model that below 0.5 Mb the variance in measurement increases significantly. We find that a subset of patients exhibits high TMB across almost all types of cancer, including many rare tumor types, and characterize the relationship between high TMB and microsatellite instability status. We find that TMB increases significantly with age, showing a 2.4-fold difference between age 10 and age 90 years. Finally, we investigate the molecular basis of TMB and identify genes and mutations associated with TMB level. We identify a cluster of somatic mutations in the promoter of the gene PMS2, which occur in 10% of skin cancers and are highly associated with increased TMB. These results show that a CGP assay targeting ~1.1 Mb of coding genome can accurately assess TMB compared with sequencing the whole exome. Using this method, we find that many disease types have a substantial portion of patients with high TMB who might benefit from immunotherapy. Finally, we identify novel, recurrent promoter mutations in PMS2, which may be another example of regulatory mutations contributing to tumorigenesis. read more read less

Topics:

Exome (54%)54% related to the paper, Exome sequencing (53%)53% related to the paper
View PDF
1,489 Citations
open accessOpen access Journal Article DOI: 10.1186/S13073-016-0307-Y
The healthy human microbiome
Jason Lloyd-Price1, Jason Lloyd-Price2, Galeb Abu-Ali1, Curtis Huttenhower1, Curtis Huttenhower2
27 Apr 2016 - Genome Medicine

Abstract:

Humans are virtually identical in their genetic makeup, yet the small differences in our DNA give rise to tremendous phenotypic diversity across the human population. By contrast, the metagenome of the human microbiome—the total DNA content of microbes inhabiting our bodies—is quite a bit more variable, with only a third of i... Humans are virtually identical in their genetic makeup, yet the small differences in our DNA give rise to tremendous phenotypic diversity across the human population. By contrast, the metagenome of the human microbiome—the total DNA content of microbes inhabiting our bodies—is quite a bit more variable, with only a third of its constituent genes found in a majority of healthy individuals. Understanding this variability in the “healthy microbiome” has thus been a major challenge in microbiome research, dating back at least to the 1960s, continuing through the Human Microbiome Project and beyond. Cataloguing the necessary and sufficient sets of microbiome features that support health, and the normal ranges of these features in healthy populations, is an essential first step to identifying and correcting microbial configurations that are implicated in disease. Toward this goal, several population-scale studies have documented the ranges and diversity of both taxonomic compositions and functional potentials normally observed in the microbiomes of healthy populations, along with possible driving factors such as geography, diet, and lifestyle. Here, we review several definitions of a ‘healthy microbiome’ that have emerged, the current understanding of the ranges of healthy microbial diversity, and gaps such as the characterization of molecular function and the development of ecological therapies to be addressed in the future. read more read less

Topics:

Human Microbiome Project (70%)70% related to the paper, Microbiome (65%)65% related to the paper, Human microbiome (59%)59% related to the paper, Metagenomics (53%)53% related to the paper, Population (52%)52% related to the paper
View PDF
823 Citations
open accessOpen access Journal Article DOI: 10.1186/GM13
The Human Gene Mutation Database: 2008 update
22 Jan 2009 - Genome Medicine

Abstract:

The Human Gene Mutation Database (HGMD®) is a comprehensive core collection of germline mutations in nuclear genes that underlie or are associated with human inherited disease. Here, we summarize the history of the database and its current resources. By December 2008, the database contained over 85,000 different lesions detec... The Human Gene Mutation Database (HGMD®) is a comprehensive core collection of germline mutations in nuclear genes that underlie or are associated with human inherited disease. Here, we summarize the history of the database and its current resources. By December 2008, the database contained over 85,000 different lesions detected in 3,253 different genes, with new entries currently accumulating at a rate exceeding 9,000 per annum. Although originally established for the scientific study of mutational mechanisms in human genes, HGMD has since acquired a much broader utility for researchers, physicians, clinicians and genetic counselors as well as for companies specializing in biopharmaceuticals, bioinformatics and personalized genomics. HGMD was first made publicly available in April 1996, and a collaboration was initiated in 2006 between HGMD and BIOBASE GmbH. This cooperative agreement covers the exclusive worldwide marketing of the most up-to-date (subscription) version of HGMD, HGMD Professional, to academic, clinical and commercial users. read more read less

Topics:

Gene mutation (55%)55% related to the paper
View PDF
810 Citations
open accessOpen access Journal Article DOI: 10.1186/S13073-014-0090-6
SRST2: Rapid genomic surveillance for public health and hospital microbiology labs
20 Nov 2014 - Genome Medicine

Abstract:

Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and ... Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data. Source code is available from http://katholt.github.io/srst2/. read more read less
View PDF
688 Citations
open accessOpen access Journal Article DOI: 10.1186/S13073-016-0303-2
Impact of the gut microbiota on inflammation, obesity, and metabolic disease.
20 Apr 2016 - Genome Medicine

Abstract:

The human gut harbors more than 100 trillion microbial cells, which have an essential role in human metabolic regulation via their symbiotic interactions with the host. Altered gut microbial ecosystems have been associated with increased metabolic and immune disorders in animals and humans. Molecular interactions linking the ... The human gut harbors more than 100 trillion microbial cells, which have an essential role in human metabolic regulation via their symbiotic interactions with the host. Altered gut microbial ecosystems have been associated with increased metabolic and immune disorders in animals and humans. Molecular interactions linking the gut microbiota with host energy metabolism, lipid accumulation, and immunity have also been identified. However, the exact mechanisms that link specific variations in the composition of the gut microbiota with the development of obesity and metabolic diseases in humans remain obscure owing to the complex etiology of these pathologies. In this review, we discuss current knowledge about the mechanistic interactions between the gut microbiota, host energy metabolism, and the host immune system in the context of obesity and metabolic disease, with a focus on the importance of the axis that links gut microbes and host metabolic inflammation. Finally, we discuss therapeutic approaches aimed at reshaping the gut microbial ecosystem to regulate obesity and related pathologies, as well as the challenges that remain in this area. read more read less

Topics:

Gut flora (58%)58% related to the paper
View PDF
687 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.

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With SciSpace, you do not need a word template for Genome Medicine.

It automatically formats your research paper to Springer 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

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

Frequently asked questions

Absolutely not! With our tool, you can freely write without having to focus on LaTeX. You can write your entire paper as per the Genome Medicine guidelines and autoformat it.

Yes. The template is fully compliant as per the guidelines of this journal. Our experts at SciSpace ensure that. Also, if there's any update in the journal format guidelines, we take care of it and include that in our algorithm.

Sure. We support all the top citation styles like APA style, MLA style, Vancouver style, Harvard style, Chicago style, etc. For example, in case of this journal, when you write your paper and hit autoformat, it will automatically update your article as per the Genome Medicine citation style.

You can avail our Free Trial for 7 days. I'm sure you'll find our features very helpful. Plus, it's quite inexpensive.

Yup. You can choose the right template, copy-paste the contents from the word doc and click on auto-format. You'll have a publish-ready paper that you can download at the end.

A matter of seconds. Besides that, our intuitive editor saves a load of your time in writing and formating your manuscript.

One little Google search can get you the Word template for any journal. However, why do you need a Word template when you can write your entire manuscript on SciSpace, autoformat it as per Genome Medicine's guidelines and download the same in Word, PDF and LaTeX formats? Try us out!.

Absolutely! You can do it using our intuitive editor. It's very easy. If you need help, you can always contact our support team.

SciSpace is an online tool for now. We'll soon release a desktop version. You can also request (or upvote) any feature that you think might be helpful for you and the research community in the feature request section once you sign-up with us.

Sure. You can request any template and we'll have it up and running within a matter of 3 working days. You can find the request box in the Journal Gallery on the right sidebar under the heading, "Couldn't find the format you were looking for?".

After you have written and autoformatted your paper, you can download it in multiple formats, viz., PDF, Docx and LaTeX.

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 those factors the review board, rejection rates, frequency of inclusion in indexes, Eigenfactor, etc. You must assess all the factors and then take the final call.

SHERPA/RoMEO Database

We have extracted this data from Sherpa Romeo to help our researchers understand the access level of this journal. The following table indicates the level of access a journal has as per Sherpa Romeo 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.

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

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

Our journal submission experts are skilled in submitting papers to various international journals.

After uploading your paper on SciSpace, you would see a button to request a journal submission service for Genome Medicine.

Each submission service is completed within 4 - 5 working days.

Yes. SciSpace provides this functionality.

After signing up, you would need to import your existing references from Word or .bib file.

SciSpace would allow download of your references in Genome Medicine Endnote style, according to springer guidelines.

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Typset automatically formats your research paper to Genome Medicine formatting guidelines and citation style.

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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.

Andreas Frutiger
Researcher & Ex MS Word user
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