Firstly, it identifies the axis elements of a chart from the given text known as x and y entities.
DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification and is responsible for many biological functions.
We present iPromoter-BnCNN for identification and accurate classification of six types of promoters - sigma24, sigma28, sigma32, sigma38, sigma54, sigma70.
1 code implementation • 20 Nov 2018 • Md Mofijul Islam, Amar Debnath, Tahsin Al Sayeed, Jyotirmay Nag Setu, Md Mahmudur Rahman, Md Sadman Sakib, Md Abdur Razzaque, Md. Mosaddek Khan, Swakkhar Shatabda
In this work, we have developed a visual interactive web application, namely d-DeVIS, which helps to visualize the internal reasoning of the learning model which is trained on the audio data.
In this paper, we present FRnet-DTI, an auto encoder and a convolutional classifier for feature manipulation and drug target interaction prediction.
The performance of MEBoost has been evaluated on 12 benchmark imbalanced datasets with state of the art ensemble methods like SMOTEBoost, RUSBoost, Easy Ensemble, EUSBoost, DataBoost.
We evaluated the performance of CUSBoost algorithm with the state-of-the-art methods based on ensemble learning like AdaBoost, RUSBoost, SMOTEBoost on 13 imbalance binary and multi-class datasets with various imbalance ratios.
The problem of class imbalance along with class-overlapping has become a major issue in the domain of supervised learning.
The effectiveness of our method is tested on standard benchmark structures.
Automated Theorem Proving (ATP) is an established branch of Artificial Intelligence.
Local search methods can quickly find good quality solutions in cases where systematic search methods might take a large amount of time.
Graph partitioning, a well studied problem of parallel computing has many applications in diversified fields such as distributed computing, social network analysis, data mining and many other domains.
In this paper, we propose a new genetic algorithm for solving the Euclidean distance geometry problem for protein structure prediction given sparse NMR data.
Due to the advancements in technology number of entries in the structural database of proteins are increasing day by day.
Protein structure prediction based on Hydrophobic-Polar energy model essentially becomes searching for a conformation having a compact hydrophobic core at the center.