Results 41 to 50 of about 7,810,973 (301)

Hybrid particle swarm optimization and semi-supervised extreme learning machine for cellular network localization

International Journal of Distributed Sensor Networks, 2017
The research of localization technology based on received signal strength and machine learning has recently attracted a lot of attentions, since with the help of enough labeled training data this technology is able to achieve high positioning accuracy ...
Fagui Liu, Hengrui Qin, Xin Yang, Yi Yu
doaj   +1 more source

Design and analysis strategies for robust microbiome ageing research

FEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

Reconstructing enzyme evolution by protein engineering

FEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler, Markus R. Busch, Reinhard Sterner   +2 more
wiley   +1 more source

The need for open source software in machine learning [PDF]

, 2007
Open source tools have recently reached a level of maturity which makes them suitable for building large-scale real-world systems. At the same time, the field of machine learning has developed a large body of powerful learning algorithms for diverse ...
Ratsch, Gunnar, Scholkopf, Bernhard, Vincent, P., LeCun, Y, Ong, C., Braun, M.L., Rasmussen, Carl Edward, Rasmussen, CE, Rätsch, G., Bengio, S., Müller, K.-R., Müller, KR, LeCunn, Yann, Muller, Klaus-Robert, Vincent , P., Pereira, Fernando, Vincent, Pascal, Bottou, Leon, Pereira, F, ,, Braun, ML, Ong, CS, Rasmussen, C.E., Smola, A, Sonnenburg, S., Holmes, G, Bengio, S, Weston, Jason, Williamson, RC, Sonnenburg, S, Williamson, Robert C., Bottou, L., Holmes, G., Ong, Cheng Soon, Pereira, F., Braun, M., Sonnenburg, Soren, Smola, Alexander, Williamson, R.C., Holmes , G., Schölkopf, B, Holmes, Geoffrey, Braun, Mikio L., Bengio, Samy, Schölkopf, B., Rasmussen, C., Williamson, R., Rätch, G, Weston, J, Smola, A., Ong, C.S., Müller, K., Bottou, L, Weston, J., Vincent, P, LeCun, Y.   +55 more
core  

Emerging experimental and computational methods for studying redox‐regulated structural transitions

FEBS Letters, EarlyView.
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass, Dana Reichmann, Gábor Erdős   +2 more
wiley   +1 more source

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

Molecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

A novel deep learning diagnosis scheme for rotating machinery using adaptive local iterative filtering and ensemble hierarchical extreme learning machine

Advances in Mechanical Engineering, 2019
There are many hyper-parameters to be tuned in both machine learning model and deep learning model, and the structure of the deep learning model is large and complicated, making it extremely difficult for fault-feature extraction and classification.
Yu Tian, Xiaohui Lei, Xiaolian Liu, Mei Liu, Xin Wen, Hao Wang   +5 more
doaj   +1 more source

Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy

Molecular Oncology, EarlyView.
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen, Zhi Zhao, Henrik Horndalsveen, Maria Moksnes Bjaanæs, Bjørn Henning Grønberg, Tarje Halvorsen, Tesfaye Madebo, Marianne Aanerud, Jussi Koivunen, Kersti Oselin, Saulius Cicenas, Nina Helbekkmo, Jarkko Ahvonen, Maria Silvoniemi, Tine Norman Alver, Tonje Dalen, Åsa Kristina Öjlert, Saima Jamil Farooqi, Åslaug Helland, Vilde Drageset Haakensen   +19 more
wiley   +1 more source

Hybrid intelligent deep kernel incremental extreme learning machine based on differential evolution and multiple population grey wolf optimization methods

Automatika, 2019
Focussing on the problem that redundant nodes in the kernel incremental extreme learning machine (KI-ELM) which leads to ineffective iteration increase and reduce the learning efficiency, a novel improved hybrid intelligent deep kernel incremental ...
Di Wu, Zong Shun Qu, Feng Jiao Guo, Xiao Lin Zhu, Qin Wan   +4 more
doaj   +1 more source

Multiple-Instance Learning Approach via Bayesian Extreme Learning Machine

IEEE Access, 2020
Multiple-instance learning (MIL) can solve supervised learning tasks, where only a bag of multiple instances is labeled, instead of a single instance.
Peipei Wang, Xinqi Zheng, Junhua Ku, Chunning Wang   +3 more
doaj   +1 more source