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EN
The focus of this research is to combine statistical and machine learning tools in application to a high-throughput biological data set on ionizing radiation response. The analyzed data consist of two gene expression sets obtained in studies of radiosensitive and radioresistant breast cancer patients undergoing radiotherapy. The data sets were similar in principle; however, the treatment dose differed. It is shown that introducing mathematical adjustments in data preprocessing, differentiation and trend testing, and classification, coupled with current biological knowledge, allows efficient data analysis and obtaining accurate results. The tools used to customize the analysis workflow were batch effect filtration with empirical Bayes models, identifying gene trends through the Jonckheere–Terpstra test and linear interpolation adjustment according to specific gene profiles for multiple random validation. The application of non-standard techniques enabled successful sample classification at the rate of 93.5% and the identification of potential biomarkers of radiation response in breast cancer, which were confirmed with an independent Monte Carlo feature selection approach and by literature references. This study shows that using customized analysis workflows is a necessary step towards novel discoveries in complex fields such as personalized individual therapy.
EN
This paper describes research behind a Large-Vocabulary Continuous Speech Recognition (LVCSR) system for the transcription of Senate speeches for the Polish language. The system utilizes several components: a phonetic transcription system, language and acoustic model training systems, a Voice Activity Detector (VAD), a LVCSR decoder, and a subtitle generator and presentation system. Some of the modules relied on already available tools and some had to be made from the beginning but the authors ensured that they used the most advanced techniques they had available at the time. Finally, several experiments were performed to compare the performance of both more modern and more conventional technologies.
EN
An approach to automate the process of event transcription is suggested. Special attention is given to the system's ergonomics and usability as well as digital speech signal pre-processing. A prototype of the system is being considered and the transcription effectiveness comparison is given for transcription with traditional means and using the system under consideration.
PL
Zasugerowana została propozycja zautomatyzowania procesu transkrypcji wydarzeń. Specjalna uwaga poświęcona jest zarówno ergonomiczności i przydatności systemu jak i cyfrowemu sygnałowi mowy we wstępnym przetwarzaniu Prototyp systemu jest obecnie rozważany a efektywność transkrypcji jest porównywana z tradycyjnymi środkami transkrypcji.
PL
Znajomość budowy i właściwości kwasów nukleinowych oraz związanych z nimi procesów replikacji, transkrypcji i translacji zrewolucjonizowały badania dotyczące molekularnych podstaw życia. Również przemysł nie pozostał obojętny na coraz to nowe odkrycia, oferując naukowcom szereg komercyjnie wytwarzanych odczynników, z czego znaczącą rolę odgrywajq enzymy (polimerazy, ligazy, restryktazy itp.).
EN
The knowledge of nucleic acids' structure and properties as well as connected with DNA/RNA replication, transcription and translation, has revolutionized molecular researches. The industry is not unconcerned with that discovery and offers many commercial reagents such as enzymes (polymerases, ligases, restrictases etc.).
5
Content available remote An Automata Description of the Genetic Message Translation
EN
In this paper we present the genetic message translation in terms of automata, transformation semigroups, restricted direct product and cascade product. We give a description of the alphabets and words involved in the processes of transcription and translation. We define a Mealy automata for the translation process, providing its detailed coverings by simpler machines. This leads to an interesting structural representation of the proteins.
EN
The DNA microarray-based technique has been developed to semi-quantitatively measure the in vivo global chromatin condensation state at the resolution of a gene. Chromatin was fractionated due to the differential solubility of histone H1-containing and histone H1-free nucleosomes. A set of genes non-randomly distributed between histone H1-free (uncondensed or open) and histone H1-containing (condensed or closed) chromatin fractions has been identified. The transcript levels have been measured for the same group of genes. The correlation between transcriptional activity and chromatin fraction distribution of particular genes has been established.
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