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Related Concept Videos

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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Learning Disabilities01:25

Learning Disabilities

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Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
Dyslexia
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Language and Cognition01:27

Language and Cognition

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Related Experiment Video

Updated: Aug 7, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
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Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

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A data-fusion approach to identifying developmental dyslexia from multi-omics datasets.

Jackson Carrion1, Rohit Nandakumar1, Xiaojian Shi1,2

  • 1College of Health Solutions, Arizona State University, Phoenix, AZ 85004.

Biorxiv : the Preprint Server for Biology
|March 13, 2023
PubMed
Summary

This study used data fusion and machine learning to explore the causes of developmental dyslexia (DD). Ensemble methods outperformed traditional techniques, identifying potential genetic biomarkers for DD.

Keywords:
Data-fusionDevelopmental DyslexiaExplainable AIMachine LearningMixture of ExpertsMulti-omics

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Area of Science:

  • Neuroscience
  • Genetics
  • Computational Biology

Background:

  • Developmental dyslexia (DD) is a common learning disability affecting 5-10% of US children.
  • The complex etiology of DD hinders accurate diagnosis.
  • Multi-omics and clinical data offer a comprehensive approach to understanding DD.

Conclusions:

  • Data fusion and ensemble learning are effective for analyzing complex multi-omics and clinical data.
  • Machine learning models can aid in classifying developmental dyslexia.
  • Genetic variations in the thalamus and cerebellum may play a role in DD etiology.