Results 31 to 40 of about 151,311 (270)

Deep Probabilistic Graphical Modeling

, 2020
Probabilistic graphical modeling (PGM) provides a framework for formulating an interpretable generative process of data and expressing uncertainty about unknowns, but it lacks flexibility. Deep learning (DL) is an alternative framework for learning from data that has achieved great empirical success in recent years.
openaire   +3 more sources

Probabilistic Graphical Model Representation in Phylogenetics [PDF]

Systematic Biology, 2014
Recent years have seen a rapid expansion of the model space explored in statistical phylogenetics, emphasizing the need for new approaches to statistical model representation and software development. Clear communication and representation of the chosen model is crucial for: (1) reproducibility of an analysis, (2) model development and (3) software ...
Höhna, Sebastian, Heath, Tracy A., Boussau, Bastien, Landis, Michael J., Ronquist, Fredrik, Huelsenbeck, John P.   +5 more
openaire   +4 more sources

An Introduction to Probabilistic Graphical Models

Proceedings of the International Florida Artificial Intelligence Research Society Conference
This tutorial covers an introduction to Probabilistic Graphical Models (PGM), such as Bayesian Networks and Markov Random Fields, for reasoning under uncertainty in intelligent systems.
Luigi Portinale
doaj   +1 more source

Summarizing Complex Graphical Models of Multiple Chronic Conditions Using the Second Eigenvalue of Graph Laplacian: Algorithm Development and Validation

JMIR Medical Informatics, 2020
BackgroundIt is important but challenging to understand the interactions of multiple chronic conditions (MCC) and how they develop over time in patients and populations.
Faruqui, Syed Hasib Akhter, Alaeddini, Adel, Chang, Mike C, Shirinkam, Sara, Jaramillo, Carlos, NajafiRad, Peyman, Wang, Jing, Pugh, Mary Jo   +7 more
doaj   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

Molecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix, Daniel Samaga, Katharina Gehr, Benedek Dankó, Mohamed Schumann, Guido Drexler, Ahmed Alnatsha, Georg Beyer, Ujjwal Mahajan, Martin Selmansberger, Julia Mayerle, Claus Belka, Horst Zitzelsberger, Kirsten Lauber   +13 more
wiley   +1 more source

Graphical User Interface for the Development of Probabilistic Convolutional Neural Networks

Signals, 2023
Through the development of artificial intelligence, some capabilities of human beings have been replicated in computers. Among the developed models, convolutional neural networks stand out considerably because they make it possible for systems to have ...
Aníbal Chaves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias   +3 more
doaj   +1 more source

Factorizing Probabilistic Graphical Models Using Co-occurrence Rate [PDF]

, 2011
Factorization is of fundamental importance in the area of Probabilistic Graphical Models (PGMs). In this paper, we theoretically develop a novel mathematical concept, \textbf{C}o-occurrence \textbf{R}ate (CR), for factorizing PGMs.
Zhu, Zhemin
core   +2 more sources

Plecstatin inhibits hepatocellular carcinoma tumorigenesis and invasion through cytolinker plectin

Molecular Oncology, EarlyView.
The ruthenium‐based metallodrug plecstatin exerts its anticancer effect in hepatocellular carcinoma (HCC) primarily through selective targeting of plectin. By disrupting plectin‐mediated cytoskeletal organization, plecstatin inhibits anchorage‐dependent growth, cell polarization, and tumor cell dissemination.
Zuzana Outla, Jan Kosla, Magdalena Prechova, Lukas Frick, Patricia Bortel, Yasmin Borutzki, Andrea Bileck, Christopher Gerner, Samuel M. Meier‐Menches, Selma Osmanagic‐Myers, Martin Gregor   +10 more
wiley   +1 more source

Determining species expansion and extinction possibilities using probabilistic and graphical models

Ekológia (Bratislava), 2015
Survival of plant species is governed by a number of functions. The participation of each function in species survival and the impact of the contrary behaviour of the species vary from function to function. The probability of extinction of species varies
Chaturvedi Rajesh, Prasad P. Rama Chandra   +1 more
doaj   +1 more source

Accurate determination of node and arc multiplicities in de bruijn graphs using conditional random fields

BMC Bioinformatics, 2020
Background De Bruijn graphs are key data structures for the analysis of next-generation sequencing data. They efficiently represent the overlap between reads and hence, also the underlying genome sequence.
Aranka Steyaert, Pieter Audenaert, Jan Fostier   +2 more
doaj   +1 more source