The need to compare compound datasets arises from various scenarios, like mergers, library extension programs, gap analysis, combinatorial library design, or estimation of QSAR model applicability domains. Whereas it is relatively easy to find identical compounds in two datasets, the quantification of the overlap is not straightforward. The various approaches described include pairwise nearest ...

BACKGROUND The simulation of the data for the QTLMAS 2009 Workshop is described. Objective was to simulate observations from a growth curve which was influenced by a number of QTL. RESULTS The data consisted of markers, phenotypes and pedigree. Genotypes of 453 markers, distributed over 5 chromosomes of 1 Morgan each, were simulated for 2,025 individuals. From those, 25 individuals were paren...

BACKGROUND Objective was to simulate the data for the QTLMAS 2010 Workshop under a model that includes major additive, epistatic and parent-of-origin effects. RESULTS Data were simulated for 3226 individuals in 5 generations. Genomic data for 5 chromosomes were simulated using coalescent model. In total, the data included 10,031 SNPs, 30 additive QTLs, 2 interacting QTL pairs, and 3 imprinted...

In recent years, we have seen a significant interest in data-driven deep learning approaches for video anomaly detection, where an algorithm must determine if specific frames of contain abnormal behaviors. However, detection is particularly context-specific, and the availability representative datasets heavily limits real-world accuracy. Additionally, metrics currently reported by most state-of...

Pattern recognition systems are widely used in a host of different fields. Due to some reasons such as lack of knowledge about a method based on which the best classifier is detected for any arbitrary problem, and thanks to significant improvement in accuracy, researchers turn to ensemble methods in almost every task of pattern recognition. Classification as a major task in pattern recognition,...

This paper describes an audio and textual dataset of debating speeches, a first-of-a-kind resource for the growing research field of computational argumentation and debating technologies. We detail the process of speech recording by professional debaters, the transcription of the speeches with an Automatic Speech Recognition (ASR) system, their consequent automatic processing to produce a text ...

Large scale image dataset and deep convolutional neural network (DCNN) are two primary driving forces for the rapid progress made in generic object recognition tasks in recent years. While lots of network architectures have been continuously designed to pursue lower error rates, few efforts are devoted to enlarge existing datasets due to high labeling cost and unfair comparison issues. In this ...