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Related Concept Videos

Extraction: Advanced Methods00:56

Extraction: Advanced Methods

Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is formed in...
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
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Gene Families01:57

Gene Families

Gene families consist of groups of genes proposed to have originated from a common ancestor. Typically these arise through events in which a gene or genes are mistakenly duplicated during cell division. Unlike their parent genes (which are subject to selection pressure to maintain function), these gene copies do not need to preserve their sequences and may evolve at a relatively faster rate.
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Pre-mRNA Processing: RNA Splicing01:32

Pre-mRNA Processing: RNA Splicing

Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...
RNA Structure01:23

RNA Structure

Overview
The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
Different Types of RNA Have the Same Basic Structure
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Scanning Electron Microscopy01:07

Scanning Electron Microscopy

A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
Fundamental Principles
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Metadata extraction using text mining.

Shivani Seth1, Stefan Rüping, Stefan Wrobel

  • 1Fraunhofer IAIS, Schloss Birlinghoven, St. Augustin, Germany. shivani.seth@iais.fraunhofer.de

Studies in Health Technology and Informatics
|July 14, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a method for automatically generating metadata for Grid services from algorithm documentation. This facilitates the integration of R functions into Grid infrastructures, enhancing eScience and healthcare applications.

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Area of Science:

  • eScience
  • Bioinformatics
  • Computational Biology

Background:

  • Grid technologies offer secure, scalable frameworks for data querying, integration, and analysis in eScience and healthcare.
  • Integrating services into Grid architectures requires metadata, including access, security, and user documentation.

Purpose of the Study:

  • To investigate the extraction of relevant metadata from semi-structured textual documentation of algorithms.
  • To enable the semi-automatic conversion of R functions into Grid services using the GridR tool.

Main Methods:

  • Utilizing text mining techniques to process algorithm documentation.
  • Developing methods for metadata generation for Grid service integration.
  • Employing the GridR tool for R function to Grid service conversion.

Main Results:

  • Successfully demonstrated the extraction of essential metadata from textual descriptions.
  • Facilitated the creation of Grid services from R functions with generated metadata.
  • Showcased the GridR tool's capability in automating this process.

Conclusions:

  • Text mining offers an effective approach for metadata extraction in Grid computing.
  • Automated metadata generation streamlines the integration of R statistical functions into Grid environments.
  • This work enhances the utility of Grid technologies in eScience and healthcare data analysis.