Results 61 to 70 of about 852,410 (222)

ShcD adaptor protein drives invasion of triple negative breast cancer cells by aberrant activation of EGFR signaling

Molecular Oncology, EarlyView.
We identified adaptor protein ShcD as upregulated in triple‐negative breast cancer and found its expression to be correlated with reduced patient survival and increased invasion in cell models. Using a proteomic screen, we identified novel ShcD binding partners involved in EGFR signaling pathways.
Hayley R. Lau, Hayley S. Smith, Begüm Alural, Claire E. Martin, Laura A. New, Manali Tilak, Sara L. Banerjee, Hannah N. Robeson, Nicolas Bisson, Anne‐Claude Gingras, Jasmin Lalonde, Nina Jones   +11 more
wiley   +1 more source

On approaches to using neural networks as an object and a means of learning in primary and secondary school

RUDN Journal of Informatization in Education
Problem statement. The article analyzes scientific papers on the application of artificial intelligence in various fields of human activity and the use of neural networks in education.
Natalia A. Ortina
doaj   +1 more source

Object Detection: Training From Scratch

IEEE Access, 2020
The development of deep neural networks has driven the development of computer vision. Deep neural networks play an important role in object detection. To improve network performance, before using neural networks for object detection, they are commonly ...
Kai Zhao, Yan Zhou, Xin Chen
doaj   +1 more source

Real-Time Encrypted Traffic Classification with Deep Learning

Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2022
Confidentiality requirements of individuals and companies led to the dominance of encrypted payloads in the overall Internet traffic. Hence, traffic classification on a network became increasingly difficult as it must rely on only the packet headers ...
Onur Demir, Deniz Tuana Ergönül
doaj   +1 more source

Graph Structure of Neural Networks [PDF]

arXiv, 2020
Neural networks are often represented as graphs of connections between neurons. However, despite their wide use, there is currently little understanding of the relationship between the graph structure of the neural network and its predictive performance.
arxiv  

Targeting the AKT/mTOR pathway attenuates the metastatic potential of colorectal carcinoma circulating tumor cells in a murine xenotransplantation model

Molecular Oncology, EarlyView.
Dual targeting of AKT and mTOR using MK2206 and RAD001 reduces tumor burden in an intracardiac colon cancer circulating tumor cell xenotransplantation model. Analysis of AKT isoform‐specific knockdowns in CTC‐MCC‐41 reveals differentially regulated proteins and phospho‐proteins by liquid chromatography coupled mass spectrometry. Circulating tumor cells
Daniel J. Smit, Thais Pereira‐Veiga, Helena Brauer, Michael Horn, Paula Nissen, Thomas Mair, Bente Siebels, Hannah Voß, Ruimeng Zhuang, Marie‐Therese Haider, Desiree Loreth, Margarita Iskhakova, Bele Lindemann, Julian Kött, Laure Cayrefourcq, Jasmin Wellbrock, Hartmut Schlüter, Klaus Pantel, Catherine Alix‐Panabières, Manfred Jücker   +19 more
wiley   +1 more source

Machine learning methods as an aid in planning orthodontic treatment on the example of Cone-Beam Computed Tomography analysis: a literature review

Journal of Education, Health and Sport, 2021
Convolutional neural networks (CNNs) are used in many areas of computer vision, such as object tracking and recognition, security, military, and biomedical image analysis.
Szymon Płotka, Tomasz Włodarczyk, Ryszard Szczerba, Anna Chomiak, Oskar Komisarek   +4 more
doaj   +1 more source

Beyond digital twins: the role of foundation models in enhancing the interpretability of multiomics modalities in precision medicine

FEBS Open Bio, EarlyView.
This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi, Xin Gao, Takashi Gojobori   +2 more
wiley   +1 more source

Knockout of the mitoribosome rescue factors Ict1 or Mtrfr is viable in zebrafish but not mice: compensatory mechanisms underlying each factor's loss

FEBS Open Bio, EarlyView.
Mitochondria contain two mitoribosome rescue factors, ICT1 and MTRFR (C12orf65). ICT1 also functions as a mitoribosomal protein in mice and humans, and its loss is lethal. Although Mtrfr knockout mice could not be generated, knockout zebrafish lines for ict1 and mtrfr were established.
Nobukazu Nameki, Chika Tomisawa, Soichiro Hoshino, Hidehiko Shimizu, Masashi Abe, Sho Arai, Kanako Kuwasako, Naoki Asakawa, Yusuke Inoue, Takuro Horii, Izuho Hatada, Masakatsu Watanabe   +11 more
wiley   +1 more source

Self-Organizing Multilayered Neural Networks of Optimal Complexity [PDF]

arXiv, 2005
The principles of self-organizing the neural networks of optimal complexity is considered under the unrepresentative learning set. The method of self-organizing the multi-layered neural networks is offered and used to train the logical neural networks which were applied to the medical diagnostics.
arxiv