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Publikováno v:
Bioinformatics
Bioinformatics, 2022, 38 (8), pp.2169-2177. ⟨10.1093/bioinformatics/btac084⟩
Bioinformatics, 2022, ⟨10.1093/bioinformatics/btac084⟩
Bioinformatics, 2022, 38 (8), pp.2169-2177. ⟨10.1093/bioinformatics/btac084⟩
Bioinformatics, 2022, ⟨10.1093/bioinformatics/btac084⟩
Motivation High-throughput single-cell molecular profiling is revolutionizing biology and medicine by unveiling the diversity of cell types and states contributing to development and disease. The identification and characterization of cellular hetero
Autor:
Justin G. Chitpin, Anuradha Surendra, Thao T. Nguyen, Graeme P. Taylor, Hongbin Xu, Irina Alecu, Roberto Ortega, Julianna J. Tomlinson, Angela M. Crawley, Michaeline McGuinty, Michael G. Schlossmacher, Rachel Saunders-Pullman, Miroslava Cuperlovic-Culf, Steffany A.L. Bennett, Theodore J. Perkins
Publikováno v:
Bioinformatics. 38:1593-1599
Motivation Bioinformatic tools capable of annotating, rapidly and reproducibly, large, targeted lipidomic datasets are limited. Specifically, few programs enable high-throughput peak assessment of liquid chromatography–electrospray ionization tande
Publikováno v:
Bioinformatics (Oxford, England)
Bioinformatics (Oxford, England), 2021, ⟨10.1093/bioinformatics/btab795⟩
Bioinformatics (Oxford, England), 2021, ⟨10.1093/bioinformatics/btab795⟩
Motivation Single-cell RNA-seq (scRNAseq) datasets are characterized by large ambient dimensionality, and their analyses can be affected by various manifestations of the dimensionality curse. One of these manifestations is the hubness phenomenon, i.e
Autor:
Claire Lesieur, Lorenza Pacini
Publikováno v:
Bioinformatics
Bioinformatics, 2021, ⟨10.1093/bioinformatics/btab736⟩
Bioinformatics, Oxford University Press (OUP), 2021, ⟨10.1093/bioinformatics/btab736⟩
Bioinformatics, 2021, ⟨10.1093/bioinformatics/btab736⟩
Bioinformatics, Oxford University Press (OUP), 2021, ⟨10.1093/bioinformatics/btab736⟩
Motivation The objective is to diagnose dynamics perturbations caused by amino-acid mutations as prerequisite to assess protein functional health or drug failure, simply using network models of protein X-ray structures. Results We find that the diffe
Publikováno v:
Bioinformatics 37, 4493-4500 (2021)
Bioinformatics
Bioinformatics
Motivation Unknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative data are
Autor:
Florian Ganglberger, Yasin Kaymaz, Ming Tang, Francesc Fernandez-Albert, Timothy B. Sackton, Nathan Lawless, Christian Haslinger
Publikováno v:
Bioinformatics. 37:4431-4436
Motivation The emergence of single-cell RNA sequencing (scRNA-seq) has led to an explosion in novel methods to study biological variation among individual cells, and to classify cells into functional and biologically meaningful categories. Results He
Autor:
Thomas Gatter, Peter F. Stadler
Publikováno v:
Bioinformatics. 37:4307-4313
Motivation Accurate assembly of RNA-seq is a crucial step in many analytic tasks such as gene annotation or expression studies. Despite ongoing research, progress on traditional single sample assembly has brought no major breakthrough. Multi-sample R
Publikováno v:
Bioinformatics. 37:4548-4555
Motivation The identification and discovery of phenotypes from high content screening images is a challenging task. Earlier works use image analysis pipelines to extract biological features, supervised training methods or generate features with neura
Autor:
Yung-Keun Kwon, Hung-Cuong Trinh
Publikováno v:
Bioinformatics
Motivation It is a challenging problem in systems biology to infer both the network structure and dynamics of a gene regulatory network from steady-state gene expression data. Some methods based on Boolean or differential equation models have been pr
Autor:
Yang Young Lu, Jeff A. Bilmes, Judit Villén, William Stafford Noble, Ricard A. Rodriguez-Mias
Publikováno v:
Bioinformatics
Motivation Tandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m/z) and time axes. The most common approach to analyzin