CALL FOR PAPERS

CERTIFICATE

IMPACT FACTOR 2018

Subject Area

  • Life Sciences / Biology
  • Architecture / Building Management
  • Asian Studies
  • Business & Management
  • Chemistry
  • Computer Science
  • Economics & Finance
  • Engineering / Acoustics
  • Environmental Science
  • Agricultural Sciences
  • Pharmaceutical Sciences
  • General Sciences
  • Materials Science
  • Mathematics
  • Medicine
  • Nanotechnology & Nanoscience
  • Nonlinear Science
  • Chaos & Dynamical Systems
  • Physics
  • Social Sciences & Humanities

Why Us? >>

  • Open Access
  • Peer Reviewed
  • Rapid Publication
  • Life time hosting
  • Free promotion service
  • Free indexing service
  • More citations
  • Search engine friendly

Plagiarism Detection

IJCR is following an instant policy on rejection those received papers with plagiarism rate of more than 20%. So, All of authors and contributors must check their papers before submission to making assurance of following our anti-plagiarism policies.

Cancer prediction using hfse approach based on dna methylation over machine learning

Author: 
Nasiya, PM., 2Priya, K.V. Dr. Rajeswari, M. and Krishnadas, J.
Subject Area: 
Physical Sciences and Engineering
Abstract: 

Breast Cancer serve as one of the diseases that make a high number of deaths every year. It is the common type of all cancers and the main cause of women’s deaths worldwide. Due to the vital role of the aberrant DNA methylation during the disease development such as cancer, prediction mechanism had become essential in the recent years for early detection and diagnosis. The high-dimensionality and noisiness of the DNA methylation data may lead to the reduction of the prediction accuracy. Thus, it becomes more important in a wide range to employ robust computational tools such as feature selection and extraction methods to extract the informative features amongst thousands of them, and hence improving cancer prediction. This paper aims at predicting cancer with a hybridized feature selection and feature extraction (HFSE) techniques. The suggested approach shows a filter feature selection method called (F-score) to overcome the high-dimensionality problem of the DNA methylation data, and proposes an extraction model which employs the peaks of the mean methylation density in order to exact cancer classification and reduce training time. To evaluate the reliability of our approach, machine learning algorithms such as The naïve base and support vector machine, knn algorithms are introduced to predict cancer. The results show that, the classification accuracy improves in all cases and it also proves the reliability indirectly.

PDF file: 

IJMCE RECOMMENDATION

ONLINE PAYPAL PAYMENT

CURRENT ISSUE

NEWS

CHIEF EDITOR
Rosane Cavalcante Fragoso, Brasil
ASSOCIATE CHIEF EDITOR

   

Jean-Marc SABATIER
Chief Scientific Officer and Head of a Research Group
France

Advantages of IJCR

  • Rapid Publishing
  • Professional publishing practices
  • Indexing in leading database
  • High level of citation
  • High Qualitiy reader base
  • High level author suport

EDITORIAL BOARD

Luai Farhan Zghair
Iraq
Hasan Ali Abed Al-Zu’bi
Jordanian
Fredrick OJIJA
Tanzanian
Firuza M. Tursunkhodjaeva
Uzbekistan
Faraz Ahmed Farooqi
Saudi Arabia
Eric Randy Reyes Politud
Philippines
Elsadig Gasoom FadelAlla Elbashir
Sudan
Eapen, Asha Sarah
United State
Dr.Arun Kumar A
India
Dr. Zafar Iqbal
Pakistan
Dr. SHAHERA S.PATEL
India
Dr. Ruchika Khanna
India
Dr. Recep TAS
Turkey
Dr. Rasha Ali Eldeeb
Egypt
Dr. Pralhad Kanhaiyalal Rahangdale
India
DR. PATRICK D. CERNA
Philippines
Dr. Nicolas Padilla- Raygoza
Mexico
Dr. Mustafa Y. G. Younis
Libiya
Dr. Muhammad shoaib Ahmedani
Saudi Arabia
DR. MUHAMMAD ISMAIL MOHMAND
United State
DR. MAHESH SHIVAJI CHAVAN
India
DR. M. ARUNA
India
Dr. Lim Gee Nee
Malaysia
Dr. Jatinder Pal Singh Chawla
India
DR. IRAM BOKHARI
Pakistan
Dr. FARHAT NAZ RAHMAN
Pakistan
Dr. Devendra kumar Gupta
India
Dr. ASHWANI KUMAR DUBEY
India
Dr. Ali Seidi
Iran
Dr. Achmad Choerudin
Indonesia
Dr Ashok Kumar Verma
India
Thi Mong Diep NGUYEN
France
Dr. Muhammad Akram
Pakistan
Dr. Imran Azad
Oman
Dr. Meenakshi Malik
India
Aseel Hadi Hamzah
Iraq
Anam Bhatti
Malaysia
Md. Amir Hossain
Bangladesh
Ahmet İPEKÇİ
Turkey
Mirzadi Gohari
Iran