Results 211 to 220 of about 911,793 (268)

Neurologists-level interpretable CT-based deep neural network for prediction of hemorrhagic transformation after ischemic stroke. [PDF]

Front Neurosci
Zhang G, Jin Y, Wang M, Han X, Tu Y, Li Z, Zhao X, Zhang Q.   +7 more
europepmc   +1 more source

Engineered Protein‐Based Ionic Conductors for Sustainable Energy Storage Applications

Advanced Materials, EarlyView.
Rational incorporation of charged residues into an engineered, self‐assembling protein scaffold yields solid‐state protein films with outstanding ionic conductivity. Salt‐doping further enhances conductivity, an effect amplified in the engineered variants. These properties enable the material integration into an efficient supercapacitor.
Juan David Cortés‐Ossa, Paolo Blesio, Marcial Fernandez‐Castro, Lisa Almonte, Maxence Fernandez, Mantas Liutkus, Perumal Pandurangan, Carlos Sabater, Aitor Villaverde, Manuel Melle‐Franco, Nurit Ashkenasy, Felipe Jiménez‐Ángeles, M. Carmen Morant‐Miñana, M. Reyes Calvo, Aitziber L. Cortajarena   +14 more
wiley   +1 more source

ZiPo: A Deep Neural Network to De-Noise Single-Cell RNA Sequencing Data. [PDF]

IEEE Trans Comput Biol Bioinform
Sharifitabar M, Kazempour S, Razavian J, Sajedi S, Solhjoo S, Zare H.   +5 more
europepmc   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

PathHDNN: a pathway hierarchical-informed deep neural network framework for predicting immunotherapy response and mechanism interpretation. [PDF]

Genome Med
Li X, Pan B, He Y, Wang Z, Tang Y, Zhang Y, Wang L, Han J.   +7 more
europepmc   +1 more source

Mesoporous Silica Nanoparticles in Biomedicine: Advances and Prospects

Advanced Materials, EarlyView.
Mesoporous silica nanoparticles offer unique properties like high surface area, tunable pores, and functionalization. They excel in drug delivery, tissue engineering, and stimuli‐responsive therapies, enabling targeted and controlled treatments. With roles in cancer therapy and diagnostics, their clinical translation requires addressing challenges in ...
Miguel Manzano, María Vallet‐Regí
wiley   +1 more source

pCPPs-sADNN: predicting cell-penetrating peptides using self-attention based deep neural network. [PDF]

Sci Rep
Almusallam N, Shahid, Hayat M, Alarfaj FK.   +3 more
europepmc   +1 more source

Label‐Free SERS Fingerprinting of Neuroprotein Conformational Dynamics in Human Saliva

Advanced Materials, EarlyView.
Galvanic molecular entrapment (GME) is a label‐free method for detecting and quantifying neuroprotein conformational states. This technique enables direct surface binding and in situ hotspot generation around molecules, effectively overcoming challenges related to target localization and mismatched hotspot geometries.
Muhammad Shalahuddin Al Ja'farawy, Jun‐Yeong Yang, Chaewon Mun, Seunghun Lee, Chul Bum Cho, Yoo Hyun Um, Min‐Young Lee, Sung‐Gyu Park, Dong‐Ho Kim, Seung Ho Yang, Ho Sang Jung   +10 more
wiley   +1 more source

MeNet: A mixed-effect deep neural network for multi-environment genomic prediction of agronomic traits. [PDF]

Plant Commun
Li Y, Ren S, Li J, Lee J, Wan J, Gan X.
europepmc   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source