The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Discriminative subgraphs can be used to characterize complex graphs, construct graph classifiers and generate graph indices. The search space for discriminative subgraphs is usually prohibitively large. Most measurements of interestingness of discriminative subgraphs are neither monotonic nor antimonotonic with respect to subgraph frequencies. Therefore, branch-and-bound algorithms are unable to mine...
We have recently found that the computation time of homology-based subcellular localization can be substantially reduced by aligning profiles up to the cleavage site positions of signal peptides, mitochondrial targeting peptides, and chloro-plast transit peptides [1]. While the method can reduce the profile alignment time by as much as 20 folds, it cannot reduce the computation time spent on creating...
Random forest is an excellent ensemble learning method, which is composed of multiple decision trees grown on random input samples and splitting nodes on a random subset of features. Due to its good classification and generalization ability, random forest has achieved success in various domains. However, random forest will generate many noisy trees when it learns from the data set that has high dimension...
The reduced support vector machine (RSVM) was proposed to overcome the computational difficulties as well as to reduce the model complexity in generating a nonlinear separating surface for a massive data set. However, it selects `support vectors' randomly from the training set, this will effect the result. To overcome this shortcoming of RSVM, an improved RSVM algorithm is presented in this paper...
The functions of proteins are closely related to their subcellular locations. In the post-proteomics era, the amount of gene and protein data grows exponentially, which necessitates the prediction of subcellular localization by computational means. This paper proposes mitigating the computation burden of alignment-based approaches to subcellular localization prediction by using the information provided...
Many applications track streaming data for actionable alerts, which may include, for example, network intrusions, transaction frauds, bio-surveilence abnormalities, and so forth. Some stream classification models are built for this purpose. Due to concept drifts, maintaining a model's up-to-dateness has become one of the most challenging tasks in mining data streams. State-of-the-art approaches, including...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.