Results 41 to 50 of about 77,382 (200)

A fair experimental comparison of neural network architectures for latent representations of multi-omics for drug response prediction

BMC Bioinformatics, 2023
Background Recent years have seen a surge of novel neural network architectures for the integration of multi-omics data for prediction. Most of the architectures include either encoders alone or encoders and decoders, i.e., autoencoders of various sorts,
Tony Hauptmann, Stefan Kramer
doaj   +1 more source

Ten quick tips for avoiding pitfalls in multi-omics data integration analyses.

PLoS Computational Biology, 2023
Data are the most important elements of bioinformatics: Computational analysis of bioinformatics data, in fact, can help researchers infer new knowledge about biology, chemistry, biophysics, and sometimes even medicine, influencing treatments and ...
Davide Chicco, Fabio Cumbo, Claudio Angione   +2 more
doaj   +1 more source

Integrative omics - from data to biology

Expert Review of Proteomics, 2018
Multi-omic approaches are promising a broader view on cellular processes and a deeper understanding of biological systems. with strongly improved high-throughput methods the amounts of data generated have become huge, and their handling challenging. Area Covered: New bioinformatic tools and pipelines for the integration of data from different omics ...
Dihazi, H., Asif, A., Beißbarth, T., Bohrer, R., Feussner, K., Feussner, I., Jahn, O., Lenz, C., Majcherczyk, A., Schmidt, B., Schmitt, K., Urlaub, H., Valerius, O.   +12 more
openaire   +6 more sources

Table1_Unsupervised Multi-Omics Data Integration Methods: A Comprehensive Review.DOCX

, 2022
Through the developments of Omics technologies and dissemination of large-scale datasets, such as those from The Cancer Genome Atlas, Alzheimer’s Disease Neuroimaging Initiative, and Genotype-Tissue Expression, it is becoming increasingly possible to ...
Nasim Vahabi (11216634), George Michailidis (213584)   +1 more
core   +1 more source

Table2_Unsupervised Multi-Omics Data Integration Methods: A Comprehensive Review.DOCX

, 2022
Through the developments of Omics technologies and dissemination of large-scale datasets, such as those from The Cancer Genome Atlas, Alzheimer’s Disease Neuroimaging Initiative, and Genotype-Tissue Expression, it is becoming increasingly possible to ...
Nasim Vahabi (11216634), George Michailidis (213584)   +1 more
core   +1 more source

ArrayTrack: a free FDA bioinformatics tool to support emerging biomedical research -- an update

Human Genomics, 2010
ArrayTrack™is a Food and Drug Administration (FDA) bioinformatics tool that has been widely adopted by the research community for genomics studies. It provides an integrated environment for microarray data management, analysis and interpretation. Most of
Xu Joshua, Kelly Reagan, Fang Hong, Tong Weida   +3 more
doaj   +1 more source

Transcriptomic and metabolomic integration as a resource in grapevine to study fruit metabolite quality traits

Frontiers in Plant Science, 2022
Transcriptomics and metabolomics are methodologies being increasingly chosen to perform molecular studies in grapevine (Vitis vinifera L.), focusing either on plant and fruit development or on interaction with abiotic or biotic factors.
Stefania Savoi, Antonio Santiago, Luis Orduña, José Tomás Matus   +3 more
doaj   +1 more source

MoAGL-SA: a multi-omics adaptive integration method with graph learning and self attention for cancer subtype classification

BMC Bioinformatics
Background The integration of multi-omics data through deep learning has greatly improved cancer subtype classification, particularly in feature learning and multi-omics data integration.
Lei Cheng, Qian Huang, Zhengqun Zhu, Yanan Li, Shuguang Ge, Longzhen Zhang, Ping Gong   +6 more
doaj   +1 more source

Systems biology and multi-omics integration: viewpoints from the metabolomics research community

, 2019
The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science.
Schirra, Horst J, Horst J. Schirra, Swarup, Sanjay, Schirra, Horst J., Wishart, David, Farhana R. Pinu, David J. Beale, David Wishart, Amy M. Paten, Kouremenos, Konstantinos, Horst J. Schirra, Paten, Amy M, Beale, David J., Paten, Amy M., Pinu, Farhana R, Sanjay Swarup, Konstantinos Kouremenos, David J. Beale, Beale, David J, Farhana R. Pinu, Pinu, Farhana R., Amy M. Paten   +21 more
core   +1 more source

Statistical single cell multi-omics integration. [PDF]

, 2018
Single cell high throughput genomic measurements are revolutionizing the fields of biology and medicine, providing a means to tackle biological problems that have thus far been inaccessible, such as the systematic discovery of new cell types, the ...
Colomé-Tatché, M., F.J. Theis, Theis, F.J., M. Colomé-Tatché, Theis, F. J.   +4 more
core   +1 more source