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Genomics02:02

Genomics

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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...
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Chromatin Immunoprecipitation- ChIP02:36

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Chromatin immunoprecipitation, or ChIP, is an antibody-based technique used to identify sites on DNA that bind to transcription factors of interest or histone proteins. It also helps determine the type of histone modifications such as acetylation, phosphorylation, or methylation.
Types of ChIP
ChIP can be divided into two types - X-ChIP and N-ChIP. X-ChIP involves in vivo cross-linking of histones and regulatory proteins to DNA, fragmenting the DNA by sonication, and isolating the protein-DNA...
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Statistical Software for Data Analysis and Clinical Trials01:12

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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
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Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes02:16

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The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...
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DNA Microarrays02:34

DNA Microarrays

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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...
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Updated: Jul 31, 2025

Author Spotlight: Investigating the Role of Repetitive DNA Misregulation in Cancer Initiation and Immunotherapy Resistance
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ChroKit: a Shiny-based framework for interactive analysis, visualization and integration of genomic data.

Ottavio Croci1, Stefano Campaner1

  • 1Center for Genomic Science of CGS@SEMM, Fondazione Istituto Italiano di Tecnologia (IIT), Milan20139, Italy.

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Summary

ChroKit is a new R-based tool for analyzing genomic data from next-generation sequencing (NGS) experiments. It offers intuitive exploration, multidimensional analysis, and visualization of chromatin data, enhancing reproducibility and collaboration.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) experiments like ChIP-Seq and DNAse-Seq generate large genomic datasets.
  • Analyzing and visualizing these enriched genomic regions requires specialized tools.

Purpose of the Study:

  • To develop an interactive, web-based framework for intuitive exploration and analysis of genomic enrichment data.
  • To provide a user-friendly platform for multidimensional analysis and visualization of NGS data.

Main Methods:

  • Developed ChroKit, an R-based interactive framework.
  • Implemented functionalities for genomic region manipulation, annotation, and signal enrichment calculation.
  • Integrated unsupervised classification algorithms and logical operations for data refinement.
  • Enabled interactive plotting with 'on the fly' re-analysis capabilities.

Main Results:

  • ChroKit facilitates intuitive exploration and multidimensional analysis of genomic enrichment data.
  • The tool supports interactive visualization and 'on the fly' data re-analysis.
  • Exportable working sessions enhance reproducibility and data sharing.
  • Multiplatform deployment optimizes computational speed and multi-user access.

Conclusions:

  • ChroKit is a fast, intuitive, and versatile tool for analyzing genomic data from various NGS experiments.
  • Its user-friendly graphical interface makes it accessible to a wide range of users.
  • ChroKit promotes efficient data exploration, analysis, and collaboration within the bioinformatics community.