Results 171 to 180 of about 26,443,777 (315)

A Tree-Based Model for Addressing Sparsity and Taxa Covariance in Microbiome Compositional Count Data. [PDF]

Stat Med
Wang Z, Mao J, Ma L.
europepmc   +1 more source

ON BASELINE CONDITIONS FOR ZERO-INFLATED LONGITUDINAL COUNT DATA [PDF]

We describe a mixed-effects hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a ...
Valentina Raponi, Antonello Maruotti
core  

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

Optimising the insect trap rate of solar lights: An application of a linear mixed-effects model to count data. [PDF]

Pest Manag Sci
Saikia H, Buragohain R, Bhattacharjee D.
europepmc   +1 more source

Gut microbiota alterations in patients with non‐small‐cell lung cancer undergoing chemoradiotherapy

Molecular Oncology, EarlyView.
We investigated the impact of concurrent chemoradiotherapy (CRT) on the gut microbiota in patients with locally advanced non‐small‐cell lung cancer. Overall gut microbiota composition remained largely stable throughout CRT while antibiotic exposure may influence microbial diversity.
Hanne Marte Nymoen, Zhi Zhao, Henrik Horndalsveen, Maria Moksnes Bjaanæs, Bjørn Henning Grønberg, Tarje Halvorsen, Tesfaye Madebo, Marianne Aanerud, Jussi Koivunen, Kersti Oselin, Saulius Cicenas, Nina Helbekkmo, Jarkko Ahvonen, Maria Silvoniemi, Tine Norman Alver, Tonje Dalen, Åsa Kristina Öjlert, Saima Jamil Farooqi, Åslaug Helland, Vilde Drageset Haakensen   +19 more
wiley   +1 more source

Hierarchical Bayesian modeling of multiregion brain cell count data. [PDF]

Elife
Dimmock S, Exley BMS, Moore G, Menage L, Delogu A, Schultz SR, Warburton EC, Houghton CJ, O'Donnell C.   +8 more
europepmc   +2 more sources

A one-parameter poisson-emrem model for count data: Theory and applications to cytogenetic and COVID-19 studies. [PDF]

Sci Rep
Sindhu TN, Shafiq A, Hamouda HM, Abushal TA, Ayid YM.   +4 more
europepmc   +1 more source

A forward demeaning transformation for a dynamic count panel data model [PDF]

In this note, a forward demeaning transformation is proposed for the linear feedback model with the explanatory variables being strictly exogenous on count panel data. This transformation is analogous to that proposed by Arellano and Bover (1995) for the
Yoshitsugu Kitazawa
core  

Predictive and prognostic biomarkers of Bacillus Calmette‐Guérin therapy failure in bladder cancer patients: A systematic review

Molecular Oncology, EarlyView.
High‐risk bladder cancer is typically treated with Bacillus Calmette‐Guérin (BCG), but 30–40% of patients relapse. No FDA‐ or CE‐approved biomarkers currently predict or prognosticate BCG failure. We systematically reviewed the literature and identified 72 eligible studies, revealing several promising biomarkers associated with BCG treatment response ...
Rui Ribeiro‐Pereira, Ana Teixeira‐Marques, Rui Freitas, João A Carvalho, Sara Monteiro‐Reis, Giorgio I. Russo, Rui Henrique, Carmen Jerónimo   +7 more
wiley   +1 more source

Geographically weighted negative binomial regression for spatial count data: Methodology and application. [PDF]

MethodsX
Saifudin T, Chamidah N, Azizah N, Renianti FS, Carista N, Adyatma IY, Tianda IM.   +6 more
europepmc   +1 more source