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Related Concept Videos

Genomics02:02

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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Applications of Molecular Taxonomy

Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...

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Related Experiment Video

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Visualizing Genetic Variants, Short Targets, and Point Mutations in the Morphological Tissue Context with an RNA In Situ Hybridization Assay
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DaMold: A data-mining platform for variant annotation and visualization in molecular diagnostics research.

Ram Vinay Pandey1,2, Stephan Pabinger1, Albert Kriegner1

  • 1Health and Environment Department, Molecular Diagnostics, Austrian Institute of Technology, Vienna, Austria.

Human Mutation
|April 12, 2017
PubMed
Summary

Next-generation sequencing (NGS) generates numerous variants, making manual interpretation challenging. DaMold offers an automated solution for variant annotation and cross-referencing, streamlining clinical research data analysis.

Keywords:
Sanger sequencingdatabase cross-referencediagnostic sequencinggenetic testinghotspot mutationmutation testingnext-generation sequencingvariant annotationvariant effect prediction

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Area of Science:

  • Genomics
  • Bioinformatics
  • Clinical Research

Background:

  • Next-generation sequencing (NGS) is crucial for mutation screening, but interpreting the vast number of variants is a significant challenge.
  • Manual analysis of variants across multiple databases is time-consuming and requires specialized expertise.
  • A need exists for an automated tool to filter, annotate, and visualize variants efficiently.

Purpose of the Study:

  • To develop a user-friendly, web-based tool for automated variant annotation and cross-referencing.
  • To streamline the interpretation of variants identified through sequencing.
  • To facilitate high-throughput analysis and visualization of genetic variants.

Main Methods:

  • Developed DaMold, a web-based application and downloadable software.
  • Integrated data from 37 relevant clinical and genomic databases.
  • Supports input formats including VCF and BED for NGS and Sanger sequencing data.

Main Results:

  • DaMold provides automated filtering and annotation of genetic variants.
  • The tool compiles information from 37 diverse resources into a single interface.
  • It offers flexible input options and supports various sequencing data types.

Conclusions:

  • DaMold addresses the critical need for efficient variant interpretation in clinical research.
  • The tool simplifies the process of variant annotation, cross-referencing, and visualization.
  • It enables automated, high-throughput analysis of sequencing data for researchers.