@article {65295,
	title = {Estimating the power of sequence covariation for detecting conserved RNA structure.},
	journal = {Bioinformatics},
	volume = {36},
	year = {2020},
	month = {2020 May 01},
	pages = {3072-76},
	abstract = {<p>Pairwise sequence covariations are a signal of conserved RNA secondary structure. We describe a method for distinguishing when lack of covariation signal can be taken as evidence against a conserved RNA structure, as opposed to when a sequence alignment merely has insufficient variation to detect covariations. We find that alignments for several long noncoding RNAs previously shown to lack covariation support do have adequate covariation detection power, providing additional evidence against their proposed conserved structures.</p>
},
	issn = {1367-4803},
	doi = {10.1093/bioinformatics/btaa080},
	url = {https://doi.org/10.1093/bioinformatics/btaa080},
	author = {Rivas, Elena and Clements, Jody and Eddy, Sean R},
	editor = {Ponty, Yann}
}
@article {65720,
	title = {Extensive and spatially variable within-cell-type heterogeneity across the basolateral amygdala.},
	journal = {eLife},
	volume = {9},
	year = {2020},
	month = {2020 Sep 01},
	abstract = {<p>The basolateral amygdala complex (BLA), extensively connected with both local amygdalar nuclei as well as long-range circuits, is involved in a diverse array of functional roles. Understanding the mechanisms of such functional diversity will be greatly informed by understanding the cell-type-specific landscape of the BLA. Here, beginning with single-cell RNA sequencing, we identified both discrete and graded continuous gene-expression differences within the mouse BLA. Via in situ hybridization, we next mapped this discrete transcriptomic heterogeneity onto a sharp spatial border between the basal and lateral amygdala nuclei, and identified continuous spatial gene-expression gradients within each of these regions. These discrete and continuous spatial transformations of transcriptomic cell-type identity were recapitulated by local morphology as well as long-range connectivity. Thus, BLA excitatory neurons are a highly heterogenous collection of neurons that spatially covary in molecular, cellular, and circuit properties. This heterogeneity likely drives pronounced spatial variation in BLA computation and function.</p>
},
	issn = {2050-084X},
	doi = {10.7554/eLife.59003},
	author = {O{\textquoteright}Leary, Timothy P and Sullivan, Kaitlin E and Wang, Lihua and Clements, Jody and Lemire, Andrew L and Cembrowski, Mark S}
}
