Results 71 to 80 of about 9,437,828 (334)
Topological Data Analysis [PDF]
arXiv, 2016 Topological Data Analysis (TDA) can broadly be described as a collection of data analysis methods that find structure in data. This includes: clustering, manifold estimation, nonlinear dimension reduction, mode estimation, ridge estimation and persistent homology. This paper reviews some of these methods.
arxiv
Unraveling Mycobacterium tuberculosis acid resistance and pH homeostasis mechanisms
FEBS Letters, EarlyView.Mycobacterium tuberculosis exhibits a remarkable resilience to acid stress. In this Review, we discuss some of the molecular mechanisms and metabolic pathways used by the tubercle bacilli to adapt and resist host‐mediated acid stress. Mycobacterium tuberculosis (Mtb) is a successful pathogen that has developed a variety of strategies to survive and ...
Janïs Laudouze +3 more
wiley +1 more source
Adaptive Differential Privacy Cox-MLP Model Based on Federated Learning
MathematicsIn the data-driven healthcare sector, balancing privacy protection and model performance is critical. This paper enhances accuracy and reliability in survival analysis by integrating differential privacy, deep learning, and the Cox proportional hazards ...
Jie Niu +6 more
doaj +1 more source
Ball mapper: a shape summary for topological data analysis [PDF]
arXiv, 2019 Topological data analysis provides a collection of tools to encapsulate and summarize the shape of data. Currently it is mainly restricted to \emph{mapper algorithm} and \emph{persistent homology}. In this paper we introduce new mapper--inspired descriptor that can be applied for exploratory data analysis.
arxiv
FEBS Letters, EarlyView.The S1025 peptide is the major antidote to the YrzI toxin, which we renamed here as SpyT (Small Peptide YrzI Toxin) and SpyA (Small Peptide YrzI Antitoxin) (1). Degradation of the toxin–antitoxin spyTA mRNA, either by a translation‐dependent cleavage by the endoribonuclease Rae1 (2) or by direct attack by 3′‐exoribonucleases (3), also contributes to ...
Laetitia Gilet +4 more
wiley +1 more source
BioData Mining, 2020 Background Various combinations of ultrasonographic (US) characteristics are increasingly utilized to classify thyroid nodules. But they lack theories, and heavily depend on radiologists’ experience, and cannot correctly classify thyroid nodules.
Dan Chen +5 more
doaj +1 more source
FEBS Letters, EarlyView.α2 → 8 polysialic acid elicits poor immunogenicity. Small‐angle scattering shows a supramolecular structure with parallel‐chain binding, although in different forms at μm and mm calcium. The major histocompatibility complex requires molecular weights around 2000 Da to produce antibodies, and 2000 Da polysialic oligomers will bind in these structures ...
Kenneth A. Rubinson
wiley +1 more source
Mobile big data analysis with machine learning [PDF]
arXiv, 2018 This paper investigates to identify the requirement and the development of machine learning-based mobile big data analysis through discussing the insights of challenges in the mobile big data (MBD). Furthermore, it reviews the state-of-the-art applications of data analysis in the area of MBD. Firstly, we introduce the development of MBD.
arxiv
FEBS Letters, EarlyView.Venom peptides have shown promise in treating pain. Our study uses computer screening to identify a peptide that targets a sodium channel (NaV1.7) linked to chronic pain. We produced the peptide in the laboratory and refined its design, advancing the search for innovative pain therapies.
Gagan Sharma +8 more
wiley +1 more source
The power of microRNA regulation—insights into immunity and metabolism
FEBS Letters, EarlyView.MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto +2 more
wiley +1 more source