M. Maruf Hossain

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Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Such datasets are particularly challenging to build classifiers for, due to their very high dimensional nature and small sample size. Decision trees are a seemingly attractive(More)
This paper presents an ensemble of feature selection and classification technique for classifying two types of breast lesion, benign and malignant. Features are selected based on their area under the ROC curves (AUC) which are then classified using a hybrid hidden Markov model (HMM)-fuzzy approach. HMM generated log-likelihood values are used to generate(More)
The k-nearest neighbour (k-NN) technique, due to its inter-pretable nature, is a simple and very intuitively appealing method to address classification problems. However, choosing an appropriate distance function for k-NN can be challenging and an inferior choice can make the classifier highly vulnerable to noise in the data. In this paper, we propose a new(More)
This paper introduces a new cost function for evaluating the multi-class classifier. The new cost function facilitates both a way to visualize the performance (expected cost) of the multi-class classifier and a summary of the misclassification costs. This function overcomes the limitations of ROC in not being able to represent the classifier performance(More)
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used to map the input space into a high dimensional feature space. However, it can perform rather poorly when there are too many dimensions (e.g. for gene expression data) or when there(More)
BACKGROUND Microarray gene expression profiling has provided extensive datasets that can describe characteristics of cancer patients. An important challenge for this type of data is the discovery of gene sets which can be used as the basis of developing a clinical predictor for cancer. It is desirable that such gene sets be compact, give accurate(More)
The attraction to sugar-rich foods is influenced by conditioned flavor preferences (CFP) produced by the sweet taste of sugar (flavor-flavor learning) and the sugar's post-oral actions (flavor-nutrient) learning. Brain dopamine (DA) circuits are involved in both types of flavor learning, but to different degrees. This study investigated the role of DA(More)
Here we describe a method to fabricate a multi-channel high-throughput microchip device for measurement of quantal transmitter release from individual cells. Instead of bringing carbon-fiber electrodes to cells, the device uses a surface chemistry approach to bring cells to an array of electrochemical microelectrodes. The microelectrodes are small and(More)