Normalization of fluorescence-based quantitative real-time PCR (qPCR) data varies across quantitative gene expression studies, despite its integral role in accurate data quantification and interpretation. Identification of suitable reference genes plays an essential role in accurate qPCR normalization, as it ensures that uncorrected gene expression data reflect normalized data. The reference re...

Social media texts, such as tweets from Twitter, contain many types of nonstandard tokens, and the number of normalization approaches for handling such noisy text has been increasing. We present a method for automatically extracting pairs of a variant word and its normal form from unsegmented text on the basis of a pair-wise similarity approach. We incorporated the acquired variant-normalizatio...

Tweets often contain a large proportion of abbreviations, alternative spellings, novel words and other non-canonical language. These features are problematic for standard language analysis tools and it can be desirable to convert them to canonical form. We propose a novel text normalization model based on learning edit operations from labeled data while incorporating features induced from unlab...

For the TREC-2005 Genomics Track ad-hoc retrieval task, we report on the development of a scalable information retrieval engine based on a relational data model for the integration of structured data and text. Our objectives are to meet the need for the integrated search of heterogeneous data sets of biomedical literature and structured data found in biological databases, and to demonstrate the...

Brain mapping techniques pair similar anatomical information across individuals. In this context, spatial normalization is mainly used to reduce inter-subject differences to improve comparisons. These techniques may benefit from anatomically identified landmarks useful to drive the registration. Automatic labeling, classification or segmentation techniques provide such labels. Most of these app...

In a previous work, Multi-Environment Model based LInear Normalization, MEMLIN, was presented and it was proved to be effective to compensate environment mismatch. MEMLIN is an empirical feature vector normalization which models clean and noisy spaces by Gaussian Mixture Models (GMMs). In this algorithm, the probability of the clean model Gaussian, given the noisy model one and the noisy featur...

We show how to construct a channel-independent representation of speech that has propagated through a noisy reverberant channel. This is done by blindly rescaling the cepstral time series by a nonlinear function, with the form of this scale function being determined by previously encountered cepstra from that channel. The rescaled form of the time series is an invariant property of it in the fo...

BACKGROUND The purpose of this study was to determine the expected time to prostate specific antigen (PSA) normalization with or without neoadjuvant androgen deprivation (NAAD) therapy after treatment with intensity modulated radiotherapy (IMRT) for patients with clinically localized prostate cancer. METHODS A retrospective cohort research design was used. A total of 133 patients with clinica...

Electromyography (EMG) is normalized in relation to a reference maximum voluntary contraction (MVC) value. Different normalization techniques are available but the most reliable method for cycling movements is unknown. This study investigated the reliability of different normalization techniques for cycling analyses. Twenty-five male cyclists (age 24.13 ± 2.79 years, body height 176.22 ± 4.87 c...