Abstract Motivation: PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important subcategories, such as proteins targeted a host cell or hyperstructures/organelles. Such improvements should preferably encompassed freely web-based that can also used standalone program. Results: We...

At SIGMOD 2015, an article was presented with the title “DBSCAN Revisited: Mis-Claim, Un-Fixability, and Approximation” that won conference’s best paper award. In this technical correspondence, we want to point out some inaccuracies in way DBSCAN represented, why criticism should have been directed at assumption about performance of spatial index structures such as R-trees not algorithm can use indexes. We will also discuss relationship indexability dataset, heuristics for choosing...

Recommender systems are becoming tools of choice to select the online information relevant a given user. Collaborative filtering is most popular approach building recommender and has been successfully employed in many applications. With advent social networks, network based recommendation emerged. This assumes among users makes recommendations for user on ratings that have direct or indirect relations with As one their major benefits, approaches shown reduce problems cold start users. In...

research-article Share on Collaborative Denoising Auto-Encoders for Top-N Recommender Systems Authors: Yao Wu Simon Fraser University, Burnaby, BC, Canada CanadaView Profile , Christopher DuBois Dato Inc., Seattle, WA, USA USAView Alice X. Zheng Martin Ester Authors Info & Claims WSDM '16: Proceedings of the Ninth ACM International Conference Web Search and Data MiningFebruary 2016Pages 153–162https://doi.org/10.1145/2835776.2835837Published:08 February 2016Publication History...

Collaborative filtering is the most popular approach to build recommender systems and has been successfully employed in many applications. However, it cannot make recommendations for so-called cold start users that have rated only a very small number of items. In addition, these methods do not know how confident they are their recommendations. Trust-based recommendation assume additional knowledge trust network among can better deal with users, since need be simply connected network. On...

Abstract Motivation: PSORTb v.1.1 is the most precise bacterial localization prediction tool available. However, program's predictive coverage and recall are low method only applicable to Gram-negative bacteria. The goals of present work as follows: increase PSORTb's while maintaining existing precision level, expand it include Gram-positive bacteria then carry out a comparative analysis localization. Results: An expanded database proteins known new modules using frequent subsequence-based...

Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known clustering, however, do not really address the special problems clustering: very high dimensionality data, size databases and understandability cluster description. In this paper, we introduce a novel approach which uses frequent item (term) for clustering. Such efficiently discovered using algorithms association rule mining. To based on term sets, measure mutual overlap with respect...

A major challenge in document clustering is the extremely high dimensionality. For example, vocabulary for a set can easily be thousands of words. On other hand, each often contains small fraction words vocabulary. These features require special handlings. Another requirement hierarchical where clustered documents browsed according to increasing specificity topics. In this paper, we propose use notion frequent itemsets, which comes from association rule mining, clustering. The intuition our...

Automated prediction of bacterial protein subcellular localization is an important tool for genome annotation and drug discovery. PSORT has been one the most widely used computational methods such analysis; however, it not updated since was introduced in 1991. In addition, neither nor any other available make predictions all five sites characteristic Gram-negative bacteria. Here we present PSORT-B, version bacteria, which as a web-based application at http://www.psort.org. PSORT-B examines...

Computational prediction of the interaction between drugs and targets is a standing challenge in field drug discovery. A number rather accurate predictions were reported for various binary drug-target benchmark datasets. However, notable drawback representation data that missing endpoints non-interacting pairs are not differentiated from inactive cases, predicted levels activity depend on pre-defined binarization thresholds. In this paper, we present method called SimBoost predicts...

Historically, gene expression has been shown to be the most informative data for drug response prediction. Recent evidence suggests that integrating additional omics can improve prediction accuracy which raises question of how integrate omics. Regardless integration strategy, clinical utility and translatability are crucial. Thus, we reasoned a multi-omics approach combined with datasets would relevance.

Network representation learning (RL) aims to transform the nodes in a network into low-dimensional vector spaces while preserving inherent properties of network. Though RL has been intensively studied, most existing works focus on either structure or node attribute information. In this paper, we propose novel framework, named ANRL, incorporate both and information principled way. Specifically, neighbor enhancement autoencoder model information, which reconstructs its target neighbors instead...

The problem of detecting clusters points belonging to a spatial point process arises in many applications. In this paper, we introduce the new clustering algorithm DBCLASD (Distribution-Based Clustering LArge Spatial Databases) discover type. results experiments demonstrate that DBCLASD, contrary partitioning algorithms such as CLARANS (Clustering Large Applications based on RANdomized Search), discovers arbitrary shape. Furthermore, does not require any input parameters, contrast DBSCAN...

Today, more and product reviews become available on the Internet, e.g., review forums, discussion groups, Blogs. However, it is almost impossible for a customer to read all of different possibly even contradictory opinions make an informed decision. Therefore, mining online (opinion mining) has emerged as interesting new research direction. Extracting aspects corresponding ratings important challenge in opinion mining. An aspect attribute or component product, e.g. 'screen' digital camera....

Mining customer reviews (opinion mining) has emerged as an interesting new research direction. Most of the reviewing websites such Epinions.com provide some additional information on top review text and overall rating, including a set predefined aspects their ratings, rating guideline which shows intended interpretation numerical ratings. However, existing methods have ignored this information. We claim that using information, is freely available, along with can effectively improve accuracy...

Mobile networks enable users to post on social media services (e.g., Twitter) from anywhere. The activities of mobile involve three major entities: user, post, and location. interaction these entities is the key answer questions such as who will a message where what topic? In this paper, we address problem profiling by modeling their activities, i.e., explore topic considering spatial textual aspects user posts, predict future locations. We propose first ST (Spatial Topic) model capture...

With the explosive growth of online social networks, it is now well understood that information highly helpful to recommender systems. Social recommendation methods are capable battling critical cold-start issue, and thus can greatly improve prediction accuracy. The main intuition through trust influence, users more likely develop affinity toward items consumed by their ties. Despite considerable work in recommendation, little attention has been paid important distinctions between strong...