Results 191 to 200 of about 42,170 (301)

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Descent from a common ancestor restricts exploration of protein sequence space. [PDF]

Proc Natl Acad Sci U S A
Isakova LH, Streltsova E, Bochkareva OO, Vlasov PK, Kondrashov FA.   +4 more
europepmc   +1 more source

Instability and change detection in exponential families and generalized linear models, with a study of Atlantic tropical storms

, 2014
Y. Lu, Snigdhansu Chatterjee
openalex   +2 more sources

Applications of Structural Statistics: Geometrical Inference in Exponential Families [PDF]

, 2020
Patrick Michl
openalex  

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

A Review: Construction of Statistical Distributions. [PDF]

Entropy (Basel)
Fang KT, Lin YX, Deng YH.
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Simplified dosimetry using two-time-point kinetic modeling of ¹²⁴I-MIBG PET for ¹³¹I-MIBG therapy in neuroblastoma. [PDF]

Med Phys
Wang Y, Huh Y, Matthay KK, Vo KT, Pampaloni MH, DuBois SG, Seo Y.   +6 more
europepmc   +1 more source

Adjusting for Network Size and Composition Effects in Exponential-Family Random Graph Models.

, 2011
Krivitsky, Pavel N., Handcock, M, Morris, Martina   +2 more
openalex