Results 61 to 70 of about 23,495 (266)

How glassy are neural networks?

, 2012
In this paper we continue our investigation on the high storage regime of a neural network with Gaussian patterns. Through an exact mapping between its partition function and one of a bipartite spin glass (whose parties consist of Ising and Gaussian ...
Adriano Barra, Amit D J, Barra A, Barra A Genovese G Guerra F Tantari D, Bigus J P, Bollé D, Bovier A, Bovier A, Coolen A C C, Coolen A C C, Daniele Tantari, De Martino D Figliuzzi M De Martino A Marinari E, Francesco Guerra, Giuseppe Genovese, Guerra F, Hebb D O, Mézard M, Singh Y, Talagrand M   +18 more
core   +1 more source

Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers

Molecular Oncology, EarlyView.
This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source

Inverse Modeling for MEG/EEG data

, 2017
We provide an overview of the state-of-the-art for mathematical methods that are used to reconstruct brain activity from neurophysiological data. After a brief introduction on the mathematics of the forward problem, we discuss standard and recently ...
A Doucet, A Galka, A Gramfort, A Pascarella, A Sorrentino, A Sorrentino, A Sorrentino, C Campi, C Lamus, CJ Long, D Calvetti, DK Nguyen, E Somersalo, F Cardinale, F Pasquale de, F-H Lin, G Dassios, GR Barnes, H Murakami, JC Mosher, JC Mosher, JM Antelis, JR Wolpaw, K Sekihara, K Uutela, K Uutela, L Miao, L Rabiner, M Hämäläinen, M Kowalski, MS Hämäläinen, PJ Green, R Bouet, RG Andrzejak, S Pursiainen, S Sommariva, SC Jun, TS Tian, V Vivaldi, W Ou, X Chen   +40 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

Sliding mode control for a phase field system related to tumor growth

, 2017
In the present contribution we study the sliding mode control (SMC) problem for a diffuse interface tumor growth model coupling a viscous Cahn-Hilliard type equation for the phase variable with a reaction-diffusion equation for the nutrient.
Colli, Pierluigi, Gilardi, Gianni, Marinoschi, Gabriela, Rocca, Elisabetta   +3 more
core   +1 more source

Overview of molecular signatures of senescence and associated resources: pros and cons

FEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source

The mathematics of the tables of learning

Science & Philosophy, 2015
The "learning tables" for mathematics are an interpretation of the National Guidelines for the Licei and the Guidelines for Technical and Professional Institutes which is consistent with their scientific and regulatory principles.
Emilio Ambrisi
doaj  

DESCOBRINDO PI: DUAS ATIVIDADES BASEADAS NOS TRABALHOS DE ARQUIMEDES

Boletim Cearense de Educação e História da Matemática, 2018
Neste artigo, oferecemos algumas sugestões para atividades a partir das ideias desenvolvidas por Arquimedes (287–212 a.C.), atividades com raízes na história da Matemática que podem proporcionar uma ligação entre a Matemática de hoje com problemas e ...
Lucieli Maria Trivizoli
doaj   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

Aspectos Motivacionais na Disciplina de Cálculo Diferencial e Integral

Revista Eletrônica Teccen, 2016
Neste trabalho, investigamos a motivação e o uso de estratégias de aprendizagem como um fator que influencia o aprendizado em Cálculo Diferencial e Integral. Buscamos traçar um perfil motivacional de turmas da referida disciplina nos cursos de Engenharia
Odileia da Silva Rosa, Chang Kuo Rodrigues, Patrícia Nunes da Silva   +2 more
doaj   +1 more source