Results 61 to 70 of about 391,798 (266)

Discerning protein pools by selective staining with self‐labeling tags

open access: yesFEBS Letters, EarlyView.
Cell surface proteins have an intra‐ and extracellular pool. Combining genetic fusion to self‐labeling tags that can be addressed with small molecule fluorophores allows separating these pools. We highlight recent developments and techniques for state‐of‐the‐art interrogation of cell surface proteins in the complex tissue setting.
Kati Fischermanns, Johannes Broichhagen
wiley   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

open access: yesMolecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim   +3 more
wiley   +1 more source

Sparse Regression by Projection and Sparse Discriminant Analysis [PDF]

open access: yesJournal of Computational and Graphical Statistics, 2015
Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously.
Qi, Xin   +3 more
openaire   +3 more sources

Single‐cell DNA methylation profiling: Technologies, computation, and applications in precision oncology

open access: yesMolecular Oncology, EarlyView.
Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley   +1 more source

Multilevel Quasi-Interpolation on Chebyshev Sparse Grids

open access: yesComputation
This paper investigates the potential of utilising multilevel quasi-interpolation techniques on Chebyshev sparse grids for complex numerical computations.
Faisal Alsharif
doaj   +1 more source

Interferon beta drives therapy resistance in a patient‐derived model of high‐grade serous ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Interferon type 1 (IFN‐1) production and signaling is associated with the acquisition of therapy resistance, following chronic DNA damage, via Interferon‐related DNA damage resistance signature (IRDS) gene expression. An alternative, DNA damage‐independent role of sustained IFN‐1 mediated resistance was identified and characterized by the emergence of ...
Ashlyn Conant   +11 more
wiley   +1 more source

Regression and Multiclass Classification Using Sparse Extreme Learning Machine via Smoothing Group L1/2 Regularizer

open access: yesIEEE Access, 2020
Extreme learning machine (ELM) is a simple feedforward neural network, and it has been extensively used in applications for its extremely fast learning speed and good generalization performance.
Qinwei Fan, Lei Niu, Qian Kang
doaj   +1 more source

Spatial biology in cancer epigenetics

open access: yesMolecular Oncology, EarlyView.
Spatial epigenomics combines molecular profiling with tissue architecture to reveal how gene regulation is organized within intact tissues. In cancer, these technologies uncover the mechanisms driving tumor heterogeneity and microenvironmental interactions, opening new opportunities for biomarker discovery and precision medicine.
Eva Crespo‐García, Manel Esteller
wiley   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

open access: yesFEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill   +4 more
wiley   +1 more source

Sparse Laneformer

open access: yesCoRR
Lane detection is a fundamental task in autonomous driving, and has achieved great progress as deep learning emerges. Previous anchor-based methods often design dense anchors, which highly depend on the training dataset and remain fixed during inference. We analyze that dense anchors are not necessary for lane detection, and propose a transformer-based
Ji Liu   +9 more
openaire   +2 more sources

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