Farzana Kabir Ahmad

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The invention of DNA microarray technology has modernized the approach of biology research in such a way that scientists can now measure the expression levels of thousands of genes simultaneously in a single experiment. Although this technology has shifted a new era in molecular classification, interpreting microarray data still remain a challenging issue(More)
Understanding the mechanisms of gene regulation during breast cancer is one of the most difficult problems among oncologists because this regulation is likely comprised of complex genetic interactions. Given this complexity, a computational study using the Bayesian network technique has been employed to construct a gene regulatory network from microarray(More)
Breast cancer is a complex and heterogeneous disease due to its diverse morphological features, as well as different clinical outcome. As a result, breast cancer patients may response to different therapeutic options. Currently, difficulties in recognizing the breast cancer types lead to inefficient treatments. Generally, there are two types of breast(More)
Image segmentation has been an important and challenging issue in the field of computer vision over decades. It plays a critical role for most image analysis tasks, such as object detection and recognition. The aim of this paper is to obtain segmented image of Printed Circuit Board (PCB)’s track using mathematical morphological operation. Morphological(More)
Breast cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. In many patients, microscopic or clinically evident metastases have already occurred by the time the primary tumor is diagnosed. Chemotherapy or hormonal therapy reduces the risk of distant metastasis by onethird, but it is estimated that about 70% to 80% of(More)
Multi label classification has become a very important paradigm in the last few years because of the increasing domains that it can be applied to. Many researchers have developed many algorithms to solve the problem of multi label classification. Nerveless, there are still some stuck problems that need to be investigated in depth. The aim of this paper is(More)
Microarray technology can measure thousands of genes which are useful for biologist to study and classify the cancer cells. However, this high dimensional data consists of large number of genes to be examined in regard of small samples size. Thus, selection of relevant genes is a challenging issue in microarray data analysis and has been a central research(More)
Focusing on the use of semantic network representation, this paper presents an easy way in understanding concepts discussed in the Holy Quran. The Quran is known as the main source of knowledge and has been a major source reference for all types of problems. However, understanding the issues and the solution from the Quran is difficult due to lack of(More)
In this paper, we propose an algorithm that performs stimulus-stimulus association via reinforcement learning. In particular, we develop a recurrent network with dynamic properties of Izhikevich spiking neuron model and train the network to associate a stimulus pair using reward modulated spike-time dependent plasticity. The learning algorithm associates a(More)
Focusing on the use of Semantic Network and Conceptual Graph (CG) representations, this paper presents an easy way in understanding concepts discussed in the Holy Quran. Quran is known as the main source of knowledge and has been a major source reference for all types of problems. However understanding the issues and the solution from the Quran is diffi(More)