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関連する概念動画

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...
921
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

21.1K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
21.1K
Components of Language01:24

Components of Language

830
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.
830
Language Development01:22

Language Development

936
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...
936
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.
812
T Cell Types and Functions01:24

T Cell Types and Functions

2.6K
When T cells with CD4 markers are activated, they give rise to two types of effector cells: helper T cells and regulatory T cells. Meanwhile, T cells with CD8 markers differentiate into effector cytotoxic T cells. The differentiation of CD4 T cells into helper T cell subsets, such as Th1, Th2, and Th17 cells, is dependent on the antigen type, antigen-presenting cell, and regulatory cytokines.
Th1 cells stimulate dendritic cells to express necessary co-stimulatory molecules on their surfaces for...
2.6K

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大型言語モデル (LLM) と CytoAnalyst を使用したセル型アノテーション.

Khoi Nguyen1, Duy Tran2, Phuong Nguyen2

  • 1Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI 48201, United States.

Bioinformatics advances
|February 11, 2026
PubMed
まとめ
この要約は機械生成です。

私たちは,大型言語モデル (LLM) を使用した半自動のセル型アノテーションツールであるCytoAnalystを開発しました. このプラットフォームは,単細胞データ分析における手作業を削減し,同時に生物学的正確性を保証します.

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Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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科学分野:

  • コンピュータ生物学 コンピュータ生物学
  • バイオインフォマティックス
  • ゲノミクスゲノミクスとは

背景:

  • セル・アノテーションは単細胞データを解釈する上で極めて重要ですが,労働集約的で,専門的な専門知識が必要です.
  • 現在の方法は,人工キュレーションと多様なバイオインフォマティクスツールにより,再現性と一貫性の課題に直面しています.

研究 の 目的:

  • CytoAnalystという新しい半自動細胞型アノテーションプラットフォームを紹介する.
  • 単細胞解析における効率的かつ正確なセルアノテーションのための大規模な言語モデル (LLM) を活用する.
  • 生物学的な完全性を維持しながら,研究者の手作業の負担を軽減する.

主な方法:

  • 単細胞データは,細胞群とマーカーを特定するために,次元縮小,クラスタリング,微分分析を受けます.
  • メタのラマと構造的なプロンプトは,細胞タイプを推論するために使用されます.
  • オントロジー,組織文脈,マーカー遺伝子シグネチャは,生物学的正確性を強制する.

主要な成果:

  • CytoAnalystは,セルアノテーションにおける手作業を大幅に削減します.
  • このプラットフォームは,強制的な制約を通じて,高い生物学的精度を維持しています.
  • 品質管理,クラスタリング,軌道推論など,包括的な単細胞分析ツールのスイートを提供しています.

結論:

  • CytoAnalystは,半自動のセルタイプアノテーションのための強力でユーザーフレンドリーなソリューションを提供します.
  • LLMの統合により,単細胞データ解釈の効率と正確性が向上します.
  • CytoAnalystは自由にアクセスでき,フィールドでのより広範な採用と再現性を促進します.