Results 71 to 80 of about 938,196 (259)
Disordered but rhythmic—the role of intrinsic protein disorder in eukaryotic circadian timing
FEBS Letters, EarlyView.Unstructured domains known as intrinsically disordered regions (IDRs) are present in nearly every part of the eukaryotic core circadian oscillator. IDRs enable many diverse inter‐ and intramolecular interactions that support clock function. IDR conformations are highly tunable by post‐translational modifications and environmental conditions, which ...
Emery T. Usher, Jacqueline F. Pelham
wiley +1 more source
Protein pyrophosphorylation by inositol pyrophosphates — detection, function, and regulation
FEBS Letters, EarlyView.Protein pyrophosphorylation is an unusual signaling mechanism that was discovered two decades ago. It can be driven by inositol pyrophosphate messengers and influences various cellular processes. Herein, we summarize the research progress and challenges of this field, covering pathways found to be regulated by this posttranslational modification as ...
Sarah Lampe +3 more
wiley +1 more source
JISKA (Jurnal Informatika Sunan Kalijaga), 2022 Universities as educational institutions have very large amounts of academic data which may not be used properly. The data needs to be analyzed to produce information that can map the distribution of students.
Qomariyah, Maria Ulfah Siregar
doaj
Discriminative k-means clustering [PDF]
The 2013 International Joint Conference on Neural Networks (IJCNN), 2013 The k-means algorithm is a partitional clustering method. Over 60 years old, it has been successfully used for a variety of problems. The popularity of k-means is in large part a consequence of its simplicity and efficiency. In this paper we are inspired by these appealing properties of k-means in the development of a clustering algorithm which accepts
openaire +2 more sources
Function‐driven design of a surrogate interleukin‐2 receptor ligand
FEBS 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
Clustering Using Boosted Constrained k-Means Algorithm
Frontiers in Robotics and AI, 2018 This article proposes a constrained clustering algorithm with competitive performance and less computation time to the state-of-the-art methods, which consists of a constrained k-means algorithm enhanced by the boosting principle.
Masayuki Okabe, Seiji Yamada
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Feature Weighting in k-Means Clustering [PDF]
Machine Learning, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Modha, Dharmendra S., Spangler, W. Scott
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Time after time – circadian clocks through the lens of oscillator theory
FEBS 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
Implementasi KD-Tree K-Means Clustering untuk Klasterisasi Dokumen
Jurnal Teknik ITS, 2013 Klasterisasi dokumen adalah suatu proses pengelompokan dokumen secara otomatis dan unsupervised. Klasterisasi dokumen merupakan permasalahan yang sering ditemui dalam berbagai bidang seperti text mining dan sistem temu kembali informasi.
Eric Budiman Gosno +2 more
doaj
Selective inference for k-means clustering.
Journal of machine learning research : JMLR, 2022 We consider the problem of testing for a difference in means between clusters of observations identified via k-means clustering. In this setting, classical hypothesis tests lead to an inflated Type I error rate. In recent work, Gao et al. (2022) considered a related problem in the context of hierarchical clustering.
Chen, Yiqun T., Witten, Daniela M.
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