Example of OncoTargets and Therapy format
Recent searches

Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
Look Inside
Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format Example of OncoTargets and Therapy format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access

OncoTargets and Therapy — Template for authors

Publisher: Dove Medical Press
Categories Rank Trend in last 3 yrs
Pharmacology (medical) #67 of 246 up up by 30 ranks
Oncology #120 of 340 up up by 42 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 3584 Published Papers | 17966 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 27/06/2020
Related journals
Insights
General info
Top papers
Popular templates
Get started guide
Why choose from SciSpace
FAQ

Related Journals

open access Open Access

Springer

Quality:  
High
CiteRatio: 5.5
SJR: 1.112
SNIP: 0.926
open access Open Access

Springer

Quality:  
High
CiteRatio: 5.6
SJR: 1.254
SNIP: 0.855
open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 7.3
SJR: 1.697
SNIP: 1.019
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 4.1
SJR: 0.757
SNIP: 1.078

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.

3.337

10% from 2018

Impact factor for OncoTargets and Therapy from 2016 - 2019
Year Value
2019 3.337
2018 3.046
2017 2.656
2016 1.653
graph view Graph view
table view Table view

5.0

11% from 2019

CiteRatio for OncoTargets and Therapy from 2016 - 2020
Year Value
2020 5.0
2019 4.5
2018 4.1
2017 3.7
2016 3.2
graph view Graph view
table view Table view

insights Insights

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

insights Insights

  • CiteRatio of this journal has increased by 11% 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.

1.054

10% from 2019

SJR for OncoTargets and Therapy from 2016 - 2020
Year Value
2020 1.054
2019 0.954
2018 0.986
2017 0.967
2016 0.99
graph view Graph view
table view Table view

0.869

5% from 2019

SNIP for OncoTargets and Therapy from 2016 - 2020
Year Value
2020 0.869
2019 0.824
2018 0.835
2017 0.764
2016 0.82
graph view Graph view
table view Table view

insights Insights

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

insights Insights

  • SNIP of this journal has increased by 5% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

OncoTargets and Therapy

Guideline source: View

All company, product and service names used in this website are for identification purposes only. All product names, trademarks and registered trademarks are property of their respective owners.

Use of these names, trademarks and brands does not imply endorsement or affiliation. Disclaimer Notice

Dove Medical Press

OncoTargets and Therapy

OncoTargets and Therapy is an international, peer-reviewed journal focusing on the pathological basis of all cancers, potential targets for therapy and treatment protocols employed to improve the management of cancer patients. In terms of therapy, palliative care is also inclu...... Read More

Pharmacology (medical)

Oncology

Medicine

i
Last updated on
26 Jun 2020
i
ISSN
1178-6930
i
Impact Factor
Medium - 0.856
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
Blue faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
unsrt
i
Citation Type
Numbered
[25]
i
Bibliography Example
C. W. J. Beenakker. Specular andreev reflection in graphene. Phys. Rev. Lett., 97(6):067007, 2006.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.2147/OTT.S105862
PD-L1 expression in human cancers and its association with clinical outcomes
Xin Wang1, Feifei Teng2, Li Kong, Jinming Yu
12 Aug 2016 - OncoTargets and Therapy

Abstract:

PD-L1 is an immunoinhibitory molecule that suppresses the activation of T cells, leading to the progression of tumors. Overexpression of PD-L1 in cancers such as gastric cancer, hepatocellular carcinoma, renal cell carcinoma, esophageal cancer, pancreatic cancer, ovarian cancer, and bladder cancer is associated with poor clin... PD-L1 is an immunoinhibitory molecule that suppresses the activation of T cells, leading to the progression of tumors. Overexpression of PD-L1 in cancers such as gastric cancer, hepatocellular carcinoma, renal cell carcinoma, esophageal cancer, pancreatic cancer, ovarian cancer, and bladder cancer is associated with poor clinical outcomes. In contrast, PD-L1 expression correlates with better clinical outcomes in breast cancer and merkel cell carcinoma. The prognostic value of PD-L1 expression in lung cancer, colorectal cancer, and melanoma is controversial. Blocking antibodies that target PD-1 and PD-L1 have achieved remarkable response rates in cancer patients who have PD-L1-overexpressing tumors. However, using PD-L1 as an exclusive predictive biomarker for cancer immunotherapy is questionable due to the low accuracy of PD-L1 immunohistochemistry staining. Factors that affect the accuracy of PD-L1 immunohistochemistry staining are as follows. First, antibodies used in different studies have different sensitivity. Second, in different studies, the cut-off value of PD-L1 staining positivity is different. Third, PD-L1 expression in tumors is not uniform, and sampling time and location may affect the results of PD-L1 staining. Therefore, better understanding of tumor microenvironment and use of other biomarkers such as gene marker and combined index are necessary to better identify patients who will benefit from PD-1/PD-L1 checkpoint blockade therapy. read more read less

Topics:

Cancer (71%)71% related to the paper, CA15-3 (64%)64% related to the paper, CA19-9 (64%)64% related to the paper, Pancreatic cancer (60%)60% related to the paper, Ovarian cancer (59%)59% related to the paper
View PDF
523 Citations
open accessOpen access Journal Article DOI: 10.2147/OTT.S80733
Computer-aided classification of lung nodules on computed tomography images via deep learning technique.
Kai-Lung Hua1, Che-Hao Hsu1, Shintami Chusnul Hidayati1, Wen-Huang Cheng2, Yu-Jen Chen3
04 Aug 2015 - OncoTargets and Therapy

Abstract:

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern reco... Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. read more read less

Topics:

Deep belief network (59%)59% related to the paper, Feature (computer vision) (57%)57% related to the paper, Deep learning (54%)54% related to the paper, Image processing (52%)52% related to the paper, Convolutional neural network (51%)51% related to the paper
View PDF
444 Citations
open accessOpen access Journal Article DOI: 10.2147/OTT.S53876
Uncovering the role of p53 splice variants in human malignancy: a clinical perspective
Sylvanie Surget1, Marie P. Khoury1, Jean-Christophe Bourdon1
19 Dec 2013 - OncoTargets and Therapy

Abstract:

Thirty-five years of research on p53 gave rise to more than 68,000 articles and reviews, but did not allow the uncovering of all the mysteries that this major tumor suppressor holds. How p53 handles the different signals to decide the appropriate cell fate in response to a stress and its implication in tumorigenesis and cance... Thirty-five years of research on p53 gave rise to more than 68,000 articles and reviews, but did not allow the uncovering of all the mysteries that this major tumor suppressor holds. How p53 handles the different signals to decide the appropriate cell fate in response to a stress and its implication in tumorigenesis and cancer progression remains unclear. Nevertheless, the uncovering of p53 isoforms has opened new perspectives in the cancer research field. Indeed, the human TP53 gene encodes not only one but at least twelve p53 protein isoforms, which are produced in normal tissues through alternative initiation of translation, usage of alternative promoters, and alternative splicing. In recent years, it became obvious that the different p53 isoforms play an important role in regulating cell fate in response to different stresses in normal cells by differentially regulating gene expression. In cancer cells, abnormal expression of p53 isoforms contributes actively to cancer formation and progression, regardless of TP53 mutation status. They can also be associated with response to treatment, depending on the cell context. The determination of p53 isoform expression and p53 mutation status helps to define different subtypes within a particular cancer type, which would have different responses to treatment. Thus, the understanding of the regulation of p53 isoform expression and their biological activities in relation to the cellular context would constitute an important step toward the improvement of the diagnostic, prognostic, and predictive values of p53 in cancer treatment. This review aims to summarize the involvement of p53 isoforms in cancer and to highlight novel potential therapeutic targets. read more read less

Topics:

Cancer (53%)53% related to the paper, Carcinogenesis (53%)53% related to the paper, Alternative splicing (51%)51% related to the paper
View PDF
344 Citations
open accessOpen access Journal Article DOI: 10.2147/OTT.S161109
Role of the NFκB-signaling pathway in cancer
11 Apr 2018 - OncoTargets and Therapy

Abstract:

Cancer is a group of cells that malignantly grow and proliferate uncontrollably. At present, treatment modes for cancer mainly comprise surgery, chemotherapy, radiotherapy, molecularly targeted therapy, gene therapy, and immunotherapy. However, the curative effects of these treatments have been limited thus far by specific ch... Cancer is a group of cells that malignantly grow and proliferate uncontrollably. At present, treatment modes for cancer mainly comprise surgery, chemotherapy, radiotherapy, molecularly targeted therapy, gene therapy, and immunotherapy. However, the curative effects of these treatments have been limited thus far by specific characteristics of tumors. Abnormal activation of signaling pathways is involved in tumor pathogenesis and plays critical roles in growth, progression, and relapse of cancers. Targeted therapies against effectors in oncogenic signaling have improved the outcomes of cancer patients. NFκB is an important signaling pathway involved in pathogenesis and treatment of cancers. Excessive activation of the NFκB-signaling pathway has been documented in various tumor tissues, and studies on this signaling pathway for targeted cancer therapy have become a hot topic. In this review, we update current understanding of the NFκB-signaling pathway in cancer. read more read less

Topics:

Targeted therapy (65%)65% related to the paper, Cancer (59%)59% related to the paper, Radiation therapy (52%)52% related to the paper
View PDF
227 Citations
open accessOpen access Journal Article DOI: 10.2147/OTT.S60114
Chemotherapy-enhanced inflammation may lead to the failure of therapy and metastasis
Dinesh Vyas1, Gieric Laput1, Arpitak K Vyas1
12 Jun 2014 - OncoTargets and Therapy

Abstract:

The lack of therapy and the failure of existing therapy has been a challenge for clinicians in treating various cancers. Doxorubicin, 5-fluorouracil, cisplatin, and paclitaxel are the first-line therapy in various cancers; however, toxicity, resistance, and treatment failure limit their clinical use. Their status leads us to ... The lack of therapy and the failure of existing therapy has been a challenge for clinicians in treating various cancers. Doxorubicin, 5-fluorouracil, cisplatin, and paclitaxel are the first-line therapy in various cancers; however, toxicity, resistance, and treatment failure limit their clinical use. Their status leads us to discover and investigate more targeted therapy with more efficacy. In this article, we dissect literature from the patient perspective, the tumor biology perspective, therapy-induced metastasis, and cell data generated in the laboratory. read more read less

Topics:

Targeted therapy (61%)61% related to the paper, Cancer (51%)51% related to the paper, Chemotherapy (50%)50% related to the paper, Metastasis (50%)50% related to the paper
View PDF
226 Citations
Author Pic

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

Get MS-Word and LaTeX output to any Journal within seconds
1
Choose a template
Select a template from a library of 40,000+ templates
2
Import a MS-Word file or start fresh
It takes only few seconds to import
3
View and edit your final output
SciSpace will automatically format your output to meet journal guidelines
4
Submit directly or Download
Submit to journal directly or Download in PDF, MS Word or LaTeX

(Before submission check for plagiarism via Turnitin)

clock Less than 3 minutes

What to expect from SciSpace?

Speed and accuracy over MS Word

''

With SciSpace, you do not need a word template for OncoTargets and Therapy.

It automatically formats your research paper to Dove Medical Press formatting guidelines and citation style.

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

Time comparison

Time taken to format a paper and Compliance with guidelines

Plagiarism Reports via Turnitin

SciSpace has partnered with Turnitin, the leading provider of Plagiarism Check software.

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?

Turnitin Stats
Publisher Logos

Freedom from formatting guidelines

One editor, 100K journal formats – world's largest collection of journal templates

With such a huge verified library, what you need is already there.

publisher-logos

Easy support from all your favorite tools

OncoTargets and Therapy format uses unsrt 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 OncoTargets and Therapy in LaTeX?

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

2. Do you follow the OncoTargets and Therapy guidelines?

Yes, the template is compliant with the OncoTargets and Therapy 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 OncoTargets and Therapy?

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 OncoTargets and Therapy citation style.

4. Can I use the OncoTargets and Therapy 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 OncoTargets and Therapy.

5. Can I use a manuscript in OncoTargets and Therapy 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 OncoTargets and Therapy that you can download at the end.

6. How long does it usually take you to format my papers in OncoTargets and Therapy?

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

7. Where can I find the template for the OncoTargets and Therapy?

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 OncoTargets and Therapy'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 OncoTargets and Therapy'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. OncoTargets and Therapy an online tool or is there a desktop version?

SciSpace's OncoTargets and Therapy 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 OncoTargets and Therapy?

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 OncoTargets and Therapy?”

11. What is the output that I would get after using OncoTargets and Therapy?

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

12. Is OncoTargets and Therapy'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 OncoTargets and Therapy?

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 OncoTargets and Therapy. 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 OncoTargets and Therapy?

The 5 most common citation types in order of usage for OncoTargets and Therapy 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 OncoTargets and Therapy?

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

16. Can I download OncoTargets and Therapy 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 OncoTargets and Therapy Endnote style according to Elsevier guidelines.

Fast and reliable,
built for complaince.

Instant formatting to 100% publisher guidelines on - SciSpace.

Available only on desktops 🖥

No word template required

Typset automatically formats your research paper to OncoTargets and Therapy formatting guidelines and citation style.

Verifed journal formats

One editor, 100K journal formats.
With the largest collection of verified journal formats, what you need is already there.

Trusted by academicians

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
Use this template