The identification of blood-secretory proteins and the detection of protein biomarkers in the blood have an important clinical application *** methods for predicting blood-secretory proteins are mainly based on tradit...
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The identification of blood-secretory proteins and the detection of protein biomarkers in the blood have an important clinical application *** methods for predicting blood-secretory proteins are mainly based on traditional machine learning algorithms,and heavily rely on annotated protein *** traditional machine learning algorithms,deep learning algorithms can automatically learn better feature representations from raw data,and are expected to be more promising to predict blood-secretory *** present a novel deep learning model(DeepHBSP)combined with transfer learning by integrating a binary classification network and a ranking network to identify blood-secretory proteins from the amino acid sequence information *** loss function of DeepHBSP in the training step is designed to apply descriptive loss and compactness loss to the binary classification network and the ranking network,*** feature extraction subnetwork of DeepHBSP is composed of a multi-lane capsule ***,transfer learning is used to train a highly accurate generalized model with small samples of blood-secretory *** main contributions of this study are as follows:1)a novel deep learning architecture by integrating a binary classification network and a ranking network is proposed,superior to existing traditional machine learning algorithms and other state-of-the-art deep learning architectures for biological sequence analysis;2)the proposed model for blood-secretory protein prediction uses only amino acid sequences,overcoming the heavy dependence of existing methods on annotated protein features;3)the blood-secretory proteins predicted by our model are statistically significant compared with existing blood-based biomarkers of cancer.
This study proposes an efficient non-parametric classifier for bankruptcy prediction using an adaptive fuzzy k-nearest neighbor (FKNN) method, where the nearest neighbor k and the fuzzy strength parameter m are adapti...
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Malaria is one of the most serious diseases in the world, which is densely distributed in poverty and remote areas. In the prevention and control of malaria, active surveillance is more efficient than passive surveill...
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Zero-shot image classification, which aims to predict unseen classes whose samples have never appeared during the training phase, is crucial in the Web domain because many new web images appear on various websites. At...
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When diagnosing dynamic system represented as discrete-event systems, it needs to find what happened to the systems from observations. The behavior of system could be represented by automaton model. The diagnostic tas...
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A novel method to measure the graph similarity is proposed, where the labels, in-degrees, and out-degrees of the vertices in the graph are comprehensively considered in order to conquer the high complexity and informa...
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A new method for simulating the folding pathway of RNA secondary structure using the modified ant colony algorithmis *** a given RNA sequence,the set of all possible stems is obtained and the energy of each stem iscal...
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A new method for simulating the folding pathway of RNA secondary structure using the modified ant colony algorithmis *** a given RNA sequence,the set of all possible stems is obtained and the energy of each stem iscalculated and stored at the initial ***,a more realistic formula is used to compute the energy ofmulti-branch loop in the following *** a folding pathway is simulated,including such processes as constructionof the heuristic information,the rule of initializing the pheromone,the mechanism of choosing the initial andnext stem and the strategy of updating the pheromone between two different *** by testing RNA sequences withknown secondary structures from the public databases,we analyze the experimental data to select appropriate values *** measure indexes show that our procedure is more consistent with phylogenetically proven structures thansoftware RNAstructure sometimes and more effective than the standard Genetic Algorithm.
Traditional supervised text classifiers require a large number of manually labeled documents, which are often expensive to obtain. Recently, dataless text classification has attracted more attention, since it only req...
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The traditional RBAC model already cannot express the complicated secure access control constraint of the workflow. Based on the traditional RBAC model, a new conditioned RBAC model named as CMWRBSAC is proposed on th...
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In this paper, a novel approach for surveillance video cropping is presented. The basic idea is to obtain a trajectory that a small sub-window can take through the video, selecting the most important regions of the vi...
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In this paper, a novel approach for surveillance video cropping is presented. The basic idea is to obtain a trajectory that a small sub-window can take through the video, selecting the most important regions of the video for display on a smaller monitor. In this framework, the video content is firstly modeled by whether image frames change at each pixel. Then a shortest path algorithm is used to find the globally optimal trajectory for a cropping window. After that a second shortest path formulation is employed to find good cuts from one trajectory to another, improving the coverage of interesting events in the video content. Finally, additional techniques are demonstrated to improve the quality and efficiency of the algorithm, and results are shown on surveillance videos from PETS 2006.
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