Results 71 to 80 of about 3,767,744 (333)

Molecular bases of circadian magnesium rhythms across eukaryotes

open access: yesFEBS Letters, EarlyView.
Circadian rhythms in intracellular [Mg2+] exist across eukaryotic kingdoms. Central roles for Mg2+ in metabolism suggest that Mg2+ rhythms could regulate daily cellular energy and metabolism. In this Perspective paper, we propose that ancestral prokaryotic transport proteins could be responsible for mediating Mg2+ rhythms and posit a feedback model ...
Helen K. Feord, Gerben van Ooijen
wiley   +1 more source

Correction: Measuring Fisher Information Accurately in Correlated Neural Populations. [PDF]

open access: yesPLoS Computational Biology, 2016
[This corrects the article DOI: 10.1371/journal.pcbi.1004218.].
PLOS Computational Biology Staff
doaj   +1 more source

Interplay between circadian and other transcription factors—Implications for cycling transcriptome reprogramming

open access: yesFEBS Letters, EarlyView.
This perspective highlights emerging insights into how the circadian transcription factor CLOCK:BMAL1 regulates chromatin architecture, cooperates with other transcription factors, and coordinates enhancer dynamics. We propose an updated framework for how circadian transcription factors operate within dynamic and multifactorial chromatin landscapes ...
Xinyu Y. Nie, Jerome S. Menet
wiley   +1 more source

Correction: Sequential inference as a mode of cognition and its correlates in fronto-parietal and hippocampal brain regions. [PDF]

open access: yesPLoS Computational Biology, 2017
[This corrects the article DOI: 10.1371/journal.pcbi.1005418.].
PLOS Computational Biology Staff
doaj   +1 more source

Mechanisms of parasite‐mediated disruption of brain vessels

open access: yesFEBS Letters, EarlyView.
Parasites can affect the blood vessels of the brain, often causing serious neurological problems. This review explains how different parasites interact with and disrupt these vessels, what this means for brain health, and why these processes matter. Understanding these mechanisms may help us develop better ways to prevent or treat brain infections in ...
Leonor Loira   +3 more
wiley   +1 more source

Correction: lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites. [PDF]

open access: yesPLoS Computational Biology, 2017
[This corrects the article DOI: 10.1371/journal.pcbi.1005513.].
PLOS Computational Biology Staff
doaj   +1 more source

To Embed or Not: Network Embedding as a Paradigm in Computational Biology

open access: yesFrontiers in Genetics, 2019
Current technology is producing high throughput biomedical data at an ever-growing rate. A common approach to interpreting such data is through network-based analyses. Since biological networks are notoriously complex and hard to decipher, a growing body
W. Nelson   +5 more
semanticscholar   +1 more source

The newfound relationship between extrachromosomal DNAs and excised signal circles

open access: yesFEBS Letters, EarlyView.
Extrachromosomal DNAs (ecDNAs) contribute to the progression of many human cancers. In addition, circular DNA by‐products of V(D)J recombination, excised signal circles (ESCs), have roles in cancer progression but have largely been overlooked. In this Review, we explore the roles of ecDNAs and ESCs in cancer development, and highlight why these ...
Dylan Casey, Zeqian Gao, Joan Boyes
wiley   +1 more source

Erratum: Notification of Republication: Modeling individual time courses of thrombopoiesis during multi-cyclic chemotherapy. [PDF]

open access: yesPLoS Computational Biology, 2019
[This corrects the article DOI: 10.1371/journal.pcbi.1006775.].
PLOS Computational Biology Staff
doaj   +1 more source

Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery

open access: yesBioMed Research International, 2019
Artificial intelligence (AI) proves to have enormous potential in many areas of healthcare including research and chemical discoveries. Using large amounts of aggregated data, the AI can discover and learn further transforming these data into “usable ...
Nagasundaram Nagarajan   +5 more
semanticscholar   +1 more source

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