Results 111 to 120 of about 720,413 (297)

Identification of speculative bubbles using state-space models with Markov-switching [PDF]

In this paper we use a state-space model with Markov-switching to detect speculative bubbles in stock-price data. Our two innovations are (1) to adapt this technology to the state-space representation of a well-known present-value stock-price model, and (
Bernd Wilfling, Nael Al-Anaswah
core  

Tumor B‐cell infiltration in platinum‐treated advanced muscle‐invasive urothelial carcinoma

Molecular Oncology, EarlyView.
Bladder tumors with higher pretreatment memory B‐cell infiltration were linked to longer survival after cisplatin chemotherapy, but not carboplatin. These tumors also showed more organized immune structures (tertiary lymphoid structures) and a shared pro‐inflammatory B‐cell‐rich community, suggesting that memory B cells may help identify patients most ...
Konrad Stawiski, Júlia Perera‐Bel, Alejo Rodriguez‐Vida, Nuria Juanpere, Jihyun Lee, Daniel E. Michaud, Jennifer L. Guerriero, Kent W. Mouw, Aristotelis Bamias, Filipe L. F. Carvalho, Joaquim Bellmunt   +10 more
wiley   +1 more source

Multilevel State-Space Models Enable High Precision Event Related Potential Analysis. [PDF]

Conf Rec Asilomar Conf Signals Syst Comput, 2023
Das P, He M, Purdon PL.
europepmc   +1 more source

Weakening the nuclear envelope: Lamin B receptor in melanoma metastasis

Molecular Oncology, EarlyView.
LBR‐driven nuclear fragility supports melanoma invasion. A: Melanocyte presents low LBR (Lamin B Receptor) levels, maintaining nuclear integrity and lamina‐chromatin tethering. B: During malignant progression, upregulation of LBR clusters at the INM (Inner Nuclear Membrane) during confined migration causes local lamina weakening and cholesterol ...
Francesca Lorenzini, Maria Caterina Mione   +1 more
wiley   +1 more source

Combining multiple data sources with different biases in state-space models for population dynamics. [PDF]

Ecol Evol, 2023
Polansky L, Mitchell L, Newman KB.
europepmc   +1 more source

Statistical Software for State Space Methods

In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software.
Jacques J. F. Commandeur, Siem Jan Koopman, Marius Ooms   +2 more
core  

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

Molecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski, Liudmyla Dolinchuk, Michał Jerzak, Albert Gandurski, Tomasz Grochowski, Weronika Wojtyś, Maciej Zadrożny, Wojciech Kaźmierczak, Małgorzata Lenarcik, Marta Matejak‐Górska, Radosław Samsel, Tomasz Olesiński, Dawid Walerych   +12 more
wiley   +1 more source

An Assessment of Alternative State Space Models for Count Time Series [PDF]

This paper compares two alternative models for autocorrelated count time series. The first model can be viewed as a 'single source of error' discrete state space model, in which a time-varying parameter is specified as a function of lagged counts, with ...
Ralph D. Snyder, Gael M. Martin, Paul D. Feigin, Phillip Gould   +3 more
core  

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

Molecular 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, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

MambaLIC: State-Space Models for Efficient Remote Sensing Image Compression

Remote Sensing
Remote sensing (RS) images, characterized by their large size and rich texture, require algorithms capable of effectively integrating both global and local features for compression.
Haobo Xiong, Kai Liu, Huachao Xiao, Chongyang Ding, Feiyang Wang   +4 more
doaj   +1 more source