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Language01:16

Language

921
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
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Components of Language01:24

Components of Language

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Language Development01:22

Language Development

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
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Language and Cognition01:27

Language and Cognition

812
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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Higher Mental Functions of the Brain: Language01:10

Higher Mental Functions of the Brain: Language

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Language is a system of communication that allows the expression of thoughts, ideas, and feelings. The brain processes language in both hemispheres.
Language formation and comprehension take place in the dominant hemisphere. The dominant hemisphere is responsible for understanding the meaning of spoken, written, or sign language, as well as the ability to communicate. For most people, the left hemisphere is the dominant one. The right hemisphere, then, gives tone and emotional context to the...
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Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Related Experiment Video

Updated: Feb 13, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

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Large language models for bioinformatics.

Wei Ruan1, Yanjun Lyu2, Jing Zhang2

  • 1School of Computing University of Georgia Athens Georgia USA.

Quantitative Biology (Beijing, China)
|February 12, 2026
PubMed
Summary
This summary is machine-generated.

Bioinformatics-specific language models (BioLMs) are rapidly advancing, offering new tools for disease diagnosis and drug discovery. This review analyzes BioLM evolution, applications, challenges, and future directions in bioinformatics.

Keywords:
bioinformatics‐specific language modelsbiological systemsbiomedical AIlarge language modelslife active factors

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Artificial Intelligence in Medicine

Background:

  • Large language models (LLMs) are rapidly evolving.
  • Bioinformatics-specific language models (BioLMs) are emerging as powerful tools.
  • A comprehensive analysis of BioLMs is needed.

Purpose of the Study:

  • To provide a thorough review of BioLMs.
  • To analyze their evolution, classification, and features.
  • To examine training methodologies, datasets, and evaluation frameworks.

Main Methods:

  • Literature review and analysis of existing BioLMs.
  • Classification of BioLMs based on architecture and application.
  • Examination of training data, computational methods, and evaluation metrics.

Main Results:

  • BioLMs have diverse applications in disease diagnosis, drug discovery, and vaccine development.
  • Key challenges include data privacy, interpretability, bias, and domain adaptation.
  • Emerging trends point towards more sophisticated biological and clinical applications.

Conclusions:

  • BioLMs hold transformative potential in bioinformatics and clinical practice.
  • Addressing challenges is crucial for responsible development and deployment.
  • Future research should focus on advancing BioLMs for complex biological problems.