Search Results for author: Swakkhar Shatabda

Found 16 papers, 4 papers with code

i6mA-CNN: a convolution based computational approach towards identification of DNA N6-methyladenine sites in rice genome

no code implementations20 Jul 2020 Ruhul Amin, Chowdhury Rafeed Rahman, Md. Sadrul Islam Toaha, Swakkhar Shatabda

DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification and is responsible for many biological functions.

A Gray Box Interpretable Visual Debugging Approach for Deep Sequence Learning Model

1 code implementation20 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.

Decision Making

FRnet-DTI: Deep Convolutional Neural Networks with Evolutionary and Structural Features for Drug-Target Interaction

no code implementations19 Jun 2018 Farshid Rayhan, Sajid Ahmed, Zaynab Mousavian, Dewan Md. Farid, Swakkhar Shatabda

In this paper, we present FRnet-DTI, an auto encoder and a convolutional classifier for feature manipulation and drug target interaction prediction.

MEBoost: Mixing Estimators with Boosting for Imbalanced Data Classification

no code implementations18 Dec 2017 Farshid Rayhan, Sajid Ahmed, Asif Mahbub, Md. Rafsan Jani, Swakkhar Shatabda, Dewan Md. Farid, Chowdhury Mofizur Rahman

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.

BIG-bench Machine Learning Classification +1

CUSBoost: Cluster-based Under-sampling with Boosting for Imbalanced Classification

1 code implementation12 Dec 2017 Farshid Rayhan, Sajid Ahmed, Asif Mahbub, Md. Rafsan Jani, Swakkhar Shatabda, Dewan Md. Farid

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.

Ensemble Learning General Classification +1

An Efficient Genetic Algorithm for Discovering Diverse-Frequent Patterns

no code implementations19 Jul 2015 Shanjida Khatun, Hasib Ul Alam, Swakkhar Shatabda

Working with exhaustive search on large dataset is infeasible for several reasons.

Stochastic Local Search for Pattern Set Mining

no code implementations18 Dec 2014 Muktadir Hossain, Tajkia Tasnim, Swakkhar Shatabda, Dewan M. Farid

Local search methods can quickly find good quality solutions in cases where systematic search methods might take a large amount of time.

FGPGA: An Efficient Genetic Approach for Producing Feasible Graph Partitions

no code implementations17 Nov 2014 Md. Lisul Islam, Novia Nurain, Swakkhar Shatabda, M. Sohel Rahman

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.

Distributed Computing graph partitioning

GreMuTRRR: A Novel Genetic Algorithm to Solve Distance Geometry Problem for Protein Structures

no code implementations16 Nov 2014 Md. Lisul Islam, Swakkhar Shatabda, M. Sohel Rahman

In this paper, we propose a new genetic algorithm for solving the Euclidean distance geometry problem for protein structure prediction given sparse NMR data.

Protein Structure Prediction

A Hybrid Local Search for Simplified Protein Structure Prediction

no code implementations31 Oct 2013 Swakkhar Shatabda, M. A. Hakim Newton, Duc Nghia Pham, Abdul Sattar

Protein structure prediction based on Hydrophobic-Polar energy model essentially becomes searching for a conformation having a compact hydrophobic core at the center.

Protein Structure Prediction

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