Results 101 to 110 of about 11,330,431 (362)

Molecular and functional profiling unravels targetable vulnerabilities in colorectal cancer

Molecular Oncology, EarlyView.
We used whole exome and RNA‐sequencing to profile divergent genomic and transcriptomic landscapes of microsatellite stable (MSS) and microsatellite instable (MSI) colorectal cancer. Alterations were classified using a computational score for integrative cancer variant annotation and prioritization.
Efstathios‐Iason Vlachavas, Konstantinos Voutetakis, Vivian Kosmidou, Spyridon Tsikalakis, Spyridon Roditis, Konstantinos Pateas, Ryangguk Kim, Kymberleigh Pagel, Stephan Wolf, Gregor Warsow, Antonia Dimitrakopoulou‐Strauss, Georgios N. Zografos, Alexander Pintzas, Johannes Betge, Olga Papadodima, Stefan Wiemann   +15 more
wiley   +1 more source

Statistical description of domains in the Potts model [PDF]

arXiv, 2009
The Zipf power law and its connection with the inhomogeneity of the system is investigated. We describe the statistical distributions of the domain masses in the Potts model near the temperature-induced phase transition. We found that the statistical distribution near the critical point is described by the power law form with a long tail, while beyond ...
arxiv  

Precision, Reliability, and Effect Size of Slope Variance in Latent Growth Curve Models: Implications for Statistical Power Analysis

Frontiers in Psychology, 2018
Latent Growth Curve Models (LGCM) have become a standard technique to model change over time. Prediction and explanation of inter-individual differences in change are major goals in lifespan research. The major determinants of statistical power to detect
A. Brandmaier, Timo von Oertzen, Paolo Ghisletta, U. Lindenberger, C. Hertzog   +4 more
semanticscholar   +1 more source

Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression

Molecular Oncology, EarlyView.
Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park, Jae Won Oh, Hyewon Chung, Jung Won Kwon, Yi Rang Na, Kwang Pyo Kim, Seung Hyeok Seok   +6 more
wiley   +1 more source

Corrigendum: The Vacc-SeqQC project: Benchmarking RNA-Seq for clinical vaccine studies

Frontiers in Immunology, 2023
Johannes B. Goll, Steven E. Bosinger, Steven E. Bosinger, Steven E. Bosinger, Steven E. Bosinger, Travis L. Jensen, Hasse Walum, Tyler Grimes, Gregory K. Tharp, Muktha S. Natrajan, Muktha S. Natrajan, Azra Blazevic, Richard D. Head, Casey E. Gelber, Kristen J. Steenbergen, Nirav B. Patel, Patrick Sanz, Nadine G. Rouphael, Nadine G. Rouphael, Nadine G. Rouphael, Evan J. Anderson, Evan J. Anderson, Mark J. Mulligan, Mark J. Mulligan, Mark J. Mulligan, Mark J. Mulligan, Daniel F. Hoft, Daniel F. Hoft   +27 more
doaj   +1 more source

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value

Molecular Oncology, EarlyView.
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song, Zhe Wang, Guangji Zhang, Jiangxue Hou, Kaiqi Liu, Shuning Wei, Yan Li, Chunlin Zhou, Dong Lin, Min Wang, Hui Wei, Jianxiang Wang, Tao Cheng, Yingchang Mi   +13 more
wiley   +1 more source

Evaluation of autumn mist‐netting data for monitoring passerine populations in interior Alaska

Wildlife Society Bulletin, 2012
We evaluated the data from 2 autumn mist‐netting stations for monitoring passerine population trends and measuring the timing of migration. Migration‐monitoring stations were operated during autumn from 1993 to 2009 at 2 interior Alaska locations: in ...
Anna‐Marie Benson, Walter N. Johnson, Ronald P. Barry, Susan L. Guers   +3 more
doaj   +1 more source

Experiments with More Than One Random Factor: Designs, Analytic Models, and Statistical Power

Annual Review of Psychology, 2017
&NA; Traditional methods of analyzing data from psychological experiments are based on the assumption that there is a single random factor (normally participants) to which generalization is sought.
C. Judd, Jacob Westfall, D. Kenny
semanticscholar   +1 more source

Statistical Power Analysis

, 2017
Preprint of Chapter appearing as: Aberson, C. L. (2015). Statistical power analysis. In R. A. Scott & S. M. Kosslyn (Eds.) Emerging trends in the behavioral and social sciences. Hoboken, NJ: Wiley.Statistical power refers to the probability of rejecting a false null hypothesis (i.e., finding what the researcher wants to find).
openaire   +2 more sources

TOMM20 as a driver of cancer aggressiveness via oxidative phosphorylation, maintenance of a reduced state, and resistance to apoptosis

Molecular Oncology, EarlyView.
TOMM20 increases cancer aggressiveness by maintaining a reduced state with increased NADH and NADPH levels, oxidative phosphorylation (OXPHOS), and apoptosis resistance while reducing reactive oxygen species (ROS) levels. Conversely, CRISPR‐Cas9 knockdown of TOMM20 alters these cancer‐aggressive traits.
Ranakul Islam, Megan E. Roche, Zhao Lin, Diana Whitaker‐Menezes, Victor Diaz‐Barros, Eurico Serrano, Maria Paula Martinez Cantarin, Nancy J. Philp, Atrayee Basu Mallick, Ubaldo Martinez‐Outschoorn   +9 more
wiley   +1 more source