Results 171 to 180 of about 725,754 (336)

Mining Chemical Space with Generative Models for Battery Materials

open access: yesBatteries &Supercaps, EarlyView.
Revolutionizing Li‐ion battery material discovery with MatterGen, a foundational generative AI model for crystal structure inverse design. Explored stable, unique, and novel compositions and their analysis with respect to the state‐of‐the‐art databases, followed by DFT validation, provides a new direction for accelerating materials discovery ...
Chiku Parida   +3 more
wiley   +1 more source

meta-MEME: Motif-based hidden Markov models of protein families [PDF]

open access: bronze, 1997
William Noble Grundy   +3 more
openalex   +1 more source

Generative Deep Learning for Advanced Battery Materials

open access: yesBatteries &Supercaps, EarlyView.
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal   +3 more
wiley   +1 more source

The hidden Markov model and its applications in bioinformatics analysis. [PDF]

open access: yesGenes Dis
Ma Y   +17 more
europepmc   +1 more source

Prediction of neutrophil nadir and recovery following paediatric haematopoietic cell transplantation with busulfan conditioning

open access: yesBritish Journal of Clinical Pharmacology, EarlyView.
Aims In haematopoietic cell transplantation (HCT), neutropenia resulting from myelosuppression is an expected endpoint following busulfan‐based conditioning. However, if prolonged, neutropenia can lead to complications like serious infection and death.
Beth Apsel Winger   +6 more
wiley   +1 more source

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