Results 31 to 40 of about 610,735 (230)

Hydro-power generation forecast in South Africa based on Machine Learning (ML) models

Scientific African, 2023
With the advancement of technology and the ever-growing need for electronics, electricity has become an indispensable aspect of modern life. Developing or underdeveloped nations must overcome a number of obstacles to balance the supply and demand for ...
Selaki Ivy Ramarope, Olawale Samuel Fatoba, Tien-Chien Jen   +2 more
doaj   +1 more source

Java-ML: a machine learning library [PDF]

, 2009
Java-ML is a collection of machine learning and data mining algorithms, which aims to be a readily usable and easily extensible API for both software developers and research scientists.
Abeel, Thomas, Van de Peer, Yves, Saeys, Yvan   +2 more
core   +1 more source

Machine Learning and Cosmological Simulations II: Hydrodynamical Simulations

, 2016
We extend a machine learning (ML) framework presented previously to model galaxy formation and evolution in a hierarchical universe using N-body + hydrodynamical simulations.
Brunner, Robert J., Kamdar, Harshil M., Turk, Matthew J.   +2 more
core   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

Molecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova, Zuzana Kozovska, Ondrej Pos, Kristina Pavlov, Sachin Gulati, Peter Makovicky, Kristina Jakic, Monika Burikova, Eva Sedlackova, Barbora Svitkova, Silvia Tyciakova, Vojtech Bystry, Nicolas Blavet, Boris Tichy, Matej Hrnciar, Jaroslav Budis, Miroslav Tomas, Peter Dubovan, Georgina Kolnikova, Veronika Repaska, Nikoleta Mojzesova, Eva Zomborska, Daniel Pindak, Michal Mego, Tomas Szemes, Miroslava Matuskova   +25 more
wiley   +1 more source

Digital twins to accelerate target identification and drug development for immune‐mediated disorders

FEBS Open Bio, EarlyView.
Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley   +1 more source

Rapid screening of staphylokinase protein variants using an unpurified cell‐free expression system

FEBS Open Bio, EarlyView.
An unpurified cell‐free protein synthesis (CFPS) platform enables rapid functional screening of staphylokinase variants. Direct plasminogen‐activation assays performed in microplate format provide real‐time activity readouts, allowing rapid identification and ranking of variants with improved or reduced fibrinolytic activity without protein ...
Maria Tomková, Veronika Hovanová, Jiri Damborsky, Erik Sedlák   +3 more
wiley   +1 more source

Machine Learning Techniques for Prognosis Estimation and Knowledge Discovery From Lab Test Results With Application to the COVID-19 Emergency

IEEE Access, 2023
AI and Machine Learning (ML) offer powerful tools to support clinical decision making in emergency situations such as the COVID-19 pandemic. In this context, the application of ML requires to design predictive systems that have adequate accuracy and can ...
Alfonso Emilio Gerevini, Roberto Maroldi, Matteo Olivato, Luca Putelli, Ivan Serina   +4 more
doaj   +1 more source

Machine learning-guided directed evolution for protein engineering [PDF]

, 2019
Machine learning (ML)-guided directed evolution is a new paradigm for biological design that enables optimization of complex functions. ML methods use data to predict how sequence maps to function without requiring a detailed model of the underlying ...
Arnold, Frances H., Wu, Zachary, Yang, Kevin K.   +2 more
core   +1 more source

Large‐scale bidirectional arrayed genetic screens identify OXR1 and EMC4 as modifiers of αSynuclein aggregation

FEBS Open Bio, EarlyView.
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane, Lea Nikolić, Lorenzo Maraio, Thomas Goiran, Nathan Karpilovsky, Stefano Sellitto, Vangelis Bouris, Jiang‐An Yin, Ronald Melki, Edward A Fon, Adriano Aguzzi, Elena De Cecco   +11 more
wiley   +1 more source

Emerging insights into CC and CXC chemokines and their receptors in Mycobacterium tuberculosis infection

FEBS Open Bio, EarlyView.
The dual roles of CC and CXC chemokines in distinguishing active, latent, and subclinical tuberculosis were reviewed, along with an evaluation of their potential as diagnostic biomarkers and therapeutic targets to advance precision medicine in tuberculosis management. The graphical abstract was generated with AI assistance (Gemini 3.0).
Xuying Yin, Dangsheng Xiao, Jiezuan Yang
wiley   +1 more source