Hasil untuk "Biology"

A. Thiam, Robert V Farese, T. Walther

Dean P. Jones

P. Seddon, D. Armstrong, R. Maloney

H. Dingle

N. S. Talekar, A. Shelton

Jin Zhang, R. Campbell, A. Ting et al.

R. Anderson, R. May

A. Ventosa, J. J. Nieto, A. Oren

C. Dinarello

R. Adam

Neema Agrawal, P. V. Dasaradhi, A. Mohmmed et al.

J. Bilezikian, L. Raisz, G. Rodan

Basic principles - cell biology biochemistry bone re-modelling and mineral homeostasis the hormones of bone other systemic hormones that influence bone metabolism local regulators of bone molecular mechanisms of metabolic bone diseases pharmacological mechanisms of therapeutics methods in bone research.

R. Legeros

D. Adams, T. Hamilton

S. Faderl, M. Talpaz, Z. Estrov et al.

Thomas Iskratsch, Haguy Wolfenson, M. Sheetz

Y. Okabe, R. Medzhitov

J. Rutkowski, J. Stern, P. Scherer

Adipose tissue is a complex, multicellular organ that profoundly influences the function of nearly all other organ systems through its diverse metabolite and adipokine secretome. Adipocytes are the primary cell type of adipose tissue and play a key role in maintaining energy homeostasis. The efficiency with which adipose tissue responds to whole-body energetic demands reflects the ability of adipocytes to adapt to an altered nutrient environment, and has profound systemic implications. Deciphering adipocyte cell biology is an important component of understanding how the aberrant physiology of expanding adipose tissue contributes to the metabolic dysregulation associated with obesity.

R. Mercier, C. Mézard, E. Jenczewski et al.

Junting Zhou, Jin Chen, Linfeng Hao et al.

The rapid evolution of large language models (LLMs) has expanded their capabilities from basic dialogue to advanced scientific reasoning. However, existing benchmarks in biology often fail to assess a critical skill required of researchers: the ability to integrate experimental results with contextual knowledge to derive meaningful conclusions. To address this gap, we introduce BABE(Biology Arena BEnchmark), a comprehensive benchmark designed to evaluate the experimental reasoning capabilities of biological AI systems. BABE is uniquely constructed from peer-reviewed research papers and real-world biological studies, ensuring that tasks reflect the complexity and interdisciplinary nature of actual scientific inquiry. BABE challenges models to perform causal reasoning and cross-scale inference. Our benchmark provides a robust framework for assessing how well AI systems can reason like practicing scientists, offering a more authentic measure of their potential to contribute to biological research.