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Navigating freely-available software tools for metabolomics analysis
Introduction The field of metabolomics has expanded greatly over the past two decades,
both as an experimental science with applications in many areas, as well as in regards to …
both as an experimental science with applications in many areas, as well as in regards to …
[كتاب][B] Temporal data mining
T Mitsa - 2010 - taylorfrancis.com
From basic data mining concepts to state-of-the-art advances, this book covers the theory of
the subject as well as its application in a variety of fields. It discusses the incorporation of …
the subject as well as its application in a variety of fields. It discusses the incorporation of …
Real-time PCR: revolutionizing detection and expression analysis of genes
Invention of polymerase chain reaction (PCR) technology by Kary Mullis in 1984 gave birth
to real-time PCR. Real-time PCR-detection and expression analysis of gene (s) in real-time …
to real-time PCR. Real-time PCR-detection and expression analysis of gene (s) in real-time …
Systematic identification of conserved metabolites in GC/MS data for metabolomics and biomarker discovery
Analysis of metabolomic profiling data from gas chromatography− mass spectrometry
(GC/MS) measurements usually relies upon reference libraries of metabolite mass spectra to …
(GC/MS) measurements usually relies upon reference libraries of metabolite mass spectra to …
Discovering characteristic actions from on-body sensor data
We present an approach to activity discovery, the unsupervised identification and modeling
of human actions embedded in a larger sensor stream. Activity discovery can be seen as the …
of human actions embedded in a larger sensor stream. Activity discovery can be seen as the …
[PDF][PDF] Discovering multivariate motifs using subsequence density estimation and greedy mixture learning
The problem of locating motifs in real-valued, multivariate time series data involves the
discovery of sets of recurring patterns embedded in the time series. Each set is composed of …
discovery of sets of recurring patterns embedded in the time series. Each set is composed of …
Prism: An effective approach for frequent sequence mining via prime-block encoding
Sequence mining is one of the fundamental data mining tasks. In this paper we present a
novel approach for mining frequent sequences, called Prism. It utilizes a vertical approach …
novel approach for mining frequent sequences, called Prism. It utilizes a vertical approach …
Unsupervised discovery of recurring speech patterns using probabilistic adaptive metrics
Unsupervised spoken term discovery (UTD) aims at finding recurring segments of speech
from a corpus of acoustic speech data. One potential approach to this problem is to use …
from a corpus of acoustic speech data. One potential approach to this problem is to use …
Conversational informatics
One often starts something new solely with a strong belief. Such optimism may bring about
unexpected outcomes. On the one hand, one might come across a magnificent landscape …
unexpected outcomes. On the one hand, one might come across a magnificent landscape …
[PDF][PDF] Improving Activity Discovery with Automatic Neighborhood Estimation.
A fundamental problem for artificial intelligence is identifying perceptual primitives from raw
sensory signals that are useful for higher-level reasoning. We equate these primitives with …
sensory signals that are useful for higher-level reasoning. We equate these primitives with …