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The task of finding transcription start sites (TSSs) can be modeled as a classification problem. Semi-Supervised Support Vector Machines (S3VMs) are an appealing method for using unlabeled data in classification. Based incorporation prior biological knowledge for recognizing TSSs, propose a Self-Training S3VMs (ST-S3VMs) algorithm. ST-S3VM builds a SVM classifier based small amounts of labeled data...
As an important member of biometric family, the vein patterns rely on the interior biological information of the body, and therefore, cannot be easily damaged, changed or falsified. In this paper, we present a new hand vein recognition system, which extracts and combines the dorsal, palm and finger vein for personal recognition. In the proposed system, the whole infrared frontal and back images of...
Emotion perception similar to thinking, learning and remembering is consequent of complicated brain processes which are related to specific biological metabolism. Different human's emotional states are recognizable by measuring and interpreting of human physiological signals. Bio-sensors possess a number of advantages against other emotion recognition methods as they are relatively more consistent...
Ontology learning aims to facilitate the construction of ontologies by decreasing the amount of effort required to produce an ontology for a new domain. However, there are few studies that attempt to automate the entire ontology learning process from the collection of domain-specific literature, to text mining to build new ontologies or enrich existing ones. In this paper, we present a complete framework...
Neural activity is very important source for data mining and can be used as a control signal for brain-computer interfaces (BCIs). Particularly, Magnetic signals of neurons are enriched with information about the movement of different part of the body such as wrist movement. In this paper, we use MEG (Magneto encephalography) signals of two subjects recorded during wrist movement task in four directions...
Chemokine receptors represent a prime target for the development of novel therapeutic strategies in a variety of disease processes. The prediction of interesting proteins types by computational methods can provide new clues in functional studies of uncharacterized proteins without performing extensive experiments. Support vector machine (SVM) is a new kind of approach to supervised pattern classification...
In search of good classification algorithm of thermostable proteins is an important issue. In this paper, a novel classification algorithm of thermostable proteins by using Hurst exponent and SVM classifier is proposed. This method not used before is the first one integrating the physics chemistry properties, fractal property and support vector machine (SVM) classifier. For evaluating the performance...
MicroRNAs (miRNAs) are 21 or 22 nucleotides noncoding RNAs known to possess important post-transcriptional regulatory functions. Identifying targeting genes that miRNAs regulate is important for understanding their specific biological functions. Usually, miRNAs down-regulate target genes through binding to the complementary sites in the 3' untranslated region (UTR) of the targets. Since the binding...
The study of the neuronal correlates of the spontaneous alternation in perception elicited by bistable visual stimuli is promising for understanding the mechanism of neural information processing and the neural basis of visual perception and perceptual decision-making. In this paper we apply a sparse nonnegative tensor factorization (NTF) based method to extract features from the local field potential...
Gene expression data usually contains a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best discriminate biological samples of different types. In this paper, we present a two-stage selection algorithm by combining ReliefF and mRMR: In the first stage, ReliefF is applied to find a candidate gene set; In the second...
In freely moving rats, motor cortical recordings enabled the use of a closed loop system to replace paddle pressing for a directional task. In this system, firing rates were estimated from several (8-10) motor cortical neurons at several consecutive time points. These firing rates were concatenated to form a neural activity vector (NAV). The NAV was used as input to a previously trained support vector...
Gene selection is an important problem in microarray data processing. A new gene selection method based on Wilcoxon rank sum test and support vector machine (SVM) is proposed in this paper. First, Wilcoxon rank sum test is used to select a subset. Then each selected gene is trained and tested using SVM classifier with linear kernel separately, and genes with high testing accuracy rates are chosen...
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