Results 91 to 100 of about 1,274,997 (260)

Representation learning for geospatial data

open access: yesAnnals of GIS
This paper reviews representation learning for geospatial data, focusing on methods for automatically extracting meaningful features from diverse data types.
Yu Liu   +12 more
doaj   +1 more source

Function‐driven design of a surrogate interleukin‐2 receptor ligand

open access: yesFEBS Letters, EarlyView.
Interleukin (IL)‐2 signaling can be achieved and precisely fine‐tuned through the affinity, distance, and orientation of the heterodimeric receptors with their ligands. We designed a biased IL‐2 surrogate ligand that selectively promotes effector T and natural killer cell activation and differentiation. Interleukin (IL) receptors play a pivotal role in
Ziwei Tang   +9 more
wiley   +1 more source

Time after time – circadian clocks through the lens of oscillator theory

open access: yesFEBS Letters, EarlyView.
Oscillator theory bridges physics and circadian biology. Damped oscillators require external drivers, while limit cycles emerge from delayed feedback and nonlinearities. Coupling enables tissue‐level coherence, and entrainment aligns internal clocks with environmental cues.
Marta del Olmo   +2 more
wiley   +1 more source

Log-based sparse nonnegative matrix factorization for data representation. [PDF]

open access: yesKnowl Based Syst, 2022
Peng C   +5 more
europepmc   +1 more source

Multiple ETS family transcription factors bind mutant p53 via distinct interaction regions

open access: yesFEBS Letters, EarlyView.
Mutant p53 gain‐of‐function is thought to be mediated by interaction with other transcription factors. We identify multiple ETS transcription factors that can bind mutant p53 and found that this interaction can be promoted by a PXXPP motif. ETS proteins that strongly bound mutant p53 were upregulated in ovarian cancer compared to ETS proteins that ...
Stephanie A. Metcalf   +6 more
wiley   +1 more source

Improved contrastive learning model via identification of false-negatives in self-supervised learning

open access: yesETRI Journal
Self-supervised learning is a method that learns the data representation through unlabeled data. It is efficient because it learns from large-scale unla-beled data and through continuous research, performance comparable to supervised learning has been ...
Joonsun Auhn, Changsik Cho, Seon-tae Kim
doaj   +1 more source

Condensed Representations for Data Mining [PDF]

open access: yes, 2005
Condensed representations have been proposed in Mannila and Toivonen (1996) as a useful concept for the optimization of typical data-mining tasks. It appears as a key concept within the inductive database framework (Boulicaut et al., 1999; de Raedt, 2002; Imielinski & Mannila, 1996), and this article introduces this research domain, its ...
openaire   +2 more sources

The newfound relationship between extrachromosomal DNAs and excised signal circles

open access: yesFEBS Letters, EarlyView.
Extrachromosomal DNAs (ecDNAs) contribute to the progression of many human cancers. In addition, circular DNA by‐products of V(D)J recombination, excised signal circles (ESCs), have roles in cancer progression but have largely been overlooked. In this Review, we explore the roles of ecDNAs and ESCs in cancer development, and highlight why these ...
Dylan Casey, Zeqian Gao, Joan Boyes
wiley   +1 more source

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