Results 31 to 40 of about 13,346,045 (362)
miRNA‐29 regulates epidermal and mesenchymal functions in skin repair
miRNA‐29 inhibits cell‐to‐cell and cell‐to‐matrix adhesion by silencing mRNA targets. Adhesion is controlled by complex interactions between many types of molecules coded by mRNAs. This is crucial for keeping together the layers of the skin and for regenerating the skin after wounding.
Lalitha Thiagarajan+10 more
wiley +1 more source
Some Insights into Lifelong Reinforcement Learning Systems [PDF]
A lifelong reinforcement learning system is a learning system that has the ability to learn through trail-and-error interaction with the environment over its lifetime. In this paper, I give some arguments to show that the traditional reinforcement learning paradigm fails to model this type of learning system.
arxiv
Spectral Methods from Tensor Networks
A tensor network is a diagram that specifies a way to "multiply" a collection of tensors together to produce another tensor (or matrix). Many existing algorithms for tensor problems (such as tensor decomposition and tensor PCA), although they are not ...
Anandkumar Animashree+2 more
core +1 more source
We present the cellular transcription‐coupled Flp‐nick system allowing the introduction of a Top1‐mimicking cleavage complex (Flpcc) at a Flp recognition target site within a controllable LacZ gene. LacZ transcription leads to the collision of RNA polymerase II (RNAPII) with Flpcc, and this causes RNAPII stalling, ubiquitination, and degradation.
Petra Herring+6 more
wiley +1 more source
A stepwise emergence of evolution in the RNA world
How did biological evolution emerge from chemical reactions? This perspective proposes a gradual scenario of self‐organization among RNA molecules, where catalytic feedback on random mixtures plays the central role. Short oligomers cross‐ligate, and self‐assembly enables heritable variations. An event of template‐externalization marks the transition to
Philippe Nghe
wiley +1 more source
Augmented Q Imitation Learning (AQIL) [PDF]
The study of unsupervised learning can be generally divided into two categories: imitation learning and reinforcement learning. In imitation learning the machine learns by mimicking the behavior of an expert system whereas in reinforcement learning the machine learns via direct environment feedback.
arxiv
As a consequence of its capability of creating high level abstractions from data, deep learning has been effectively employed in a wide range of applications, including physics. Though deep learning can be, at first and simplistically understood in terms of very large neural networks, it also encompasses new concepts and methods. In order to understand
Arruda, Henrique F. de+3 more
openaire +4 more sources
The number of circulating tumor cells obtained from prostate cancer patients was increased approximately 5‐fold compared to regular CellSearch when processing 2 mL diagnostic leukapheresis material aliquots and increased by 44‐fold when processing 20 mL DLA aliquots using the flow enrichment target capture Halbach‐array.
Michiel Stevens+8 more
wiley +1 more source
Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever+1 more
wiley +1 more source
Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker+14 more
wiley +1 more source