تجاوز إلى المحتوى الرئيسي
User Image

Achraf El Allali

Assistant Professor

Faculty

علوم الحاسب والمعلومات
Building 31, 2nd floor, room 2119
المنشورات
ورقة مؤتمر
2019

The Effect of Machine Learning Algorithms on Metagenomics Gene Prediction

Allali, Achraf El . 2019

The development of next-generation sequencing facilitates the study of metagenomics. Computational gene prediction aims to find the location of genes in a given DNA sequence. Gene prediction in metagenomics is a challenging task because of the short and fragmented nature of the data. Our previous framework minimum redundancy maximum relevance-support vector machines (mRMR-SVM) produced promising results in metagenomics gene prediction. In this paper, we review available metagenomics gene prediction programs and study the effect of the machine learning approach on gene prediction by altering the underlining machine learning algorithm in our previous framework. Overall, SVM produces the highest accuracy based on tests performed on a simulated dataset.

موقع المؤتمر
Hong Kong
اسم المؤتمر
5th International Conference on Bioinformatics Research and Applications
مزيد من المنشورات
publications

Next-generation sequencing approaches and genome-wide studies have become essential for characterizing the mechanisms of human diseases.

2019
publications

The development of next-generation sequencing facilitates the study of metagenomics. Computational gene prediction aims to find the location of genes in a given DNA sequence. Gene prediction in…

بواسطة Achraf El Allali
2019
publications

Accurate gene prediction in metagenomics fragments is a computationally challenging task due to the short-read length, incomplete, and fragmented nature of the data. Most gene-prediction programs…

2018