Methods for constructing and evaluating consensus genomic interval sets.

The amount of genomic region data continues to increase. Integrating across diverse genomic region sets requires consensus regions, which enable comparing regions across experiments, but also by necessity lose precision in region definitions. We require methods to assess this loss of precision and build optimal consensus region sets.

PEPhub: a database, web interface, and API for editing, sharing, and validating biological sample metadata.

Background: As biological data increase, we need additional infrastructure to share them and promote interoperability. While major effort has been put into sharing data, relatively less emphasis is placed on sharing metadata. Yet, sharing metadata is also important and in some ways has a wider scope than sharing data themselves.

Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings.

Data from the single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) are now widely available. One major computational challenge is dealing with high dimensionality and inherent sparsity, which is typically addressed by producing lower dimensional representations of single cells for downstream clustering tasks. Current approaches produce such individual cell embeddings directly through a one-step learning process.

DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data.

Motivation: Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, with the cellular heterogeneity in single-cell gene profiles, current statistical GSE analysis methods sometimes fail to identify enriched gene sets.

The role of working memory capacity in the temporal compression of episodic memories: An individual differences approach.

Remembering past events usually takes less time than their actual duration-their unfolding is temporally compressed in episodic memory. The rate of temporal compression (i.e.

Working memory capacity for continuous events: The root of temporal compression in episodic memory?

Remembering the unfolding of past episodes usually takes less time than their actual duration. In this study, we evaluated whether such temporal compression emerges when continuous events are too long to be fully held in working memory. To do so, we asked 90 young adults to watch and mentally replay video clips showing people performing a continuous action (e.

Joint Representation Learning for Retrieval and Annotation of Genomic Interval Sets.

As available genomic interval data increase in scale, we require fast systems to search them. A common approach is simple string matching to compare a search term to metadata, but this is limited by incomplete or inaccurate annotations. An alternative is to compare data directly through genomic region overlap analysis, but this approach leads to challenges like sparsity, high dimensionality, and computational expense.

PEPhub: a database, web interface, and API for editing, sharing, and validating biological sample metadata.

Background: As biological data increases, we need additional infrastructure to share it and promote interoperability. While major effort has been put into sharing data, relatively less emphasis is placed on sharing metadata. Yet, sharing metadata is also important, and in some ways has a wider scope than sharing data itself.

GEOfetch: a command-line tool for downloading data and standardized metadata from GEO and SRA.

Motivation: The Gene Expression Omnibus has become an important source of biological data for secondary analysis. However, there is no simple, programmatic way to download data and metadata from Gene Expression Omnibus (GEO) in a standardized annotation format.

Results: To address this, we present GEOfetch-a command-line tool that downloads and organizes data and metadata from GEO and SRA.

GenomicDistributions: fast analysis of genomic intervals with Bioconductor.

Background: Epigenome analysis relies on defined sets of genomic regions output by widely used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of genomic region sets is essential to answer biological questions in gene regulation. As the epigenomics community continues generating data, there will be an increasing need for software tools that can efficiently deal with more abundant and larger genomic region sets.

The Neural Representation of Ordinal Information: Domain-Specific or Domain-General?

Ordinal processing allows for the representation of the sequential relations between stimuli and is a fundamental aspect of different cognitive domains such as verbal working memory (WM), language and numerical cognition. Several studies suggest common ordinal coding mechanisms across these different domains but direct between-domain comparisons of ordinal coding are rare and have led to contradictory evidence. This fMRI study examined the commonality of ordinal representations across the WM, the number, and the letter domains by using a multivoxel pattern analysis approach and by focusing on triplet stimuli associated with robust ordinal distance effects.

Neuron Activity Dependent Redox Compartmentation Revealed with a Second Generation Red-Shifted Ratiometric Sensor.

Oxidative stress is a hallmark of several aging and trauma related neurological disorders, but the precise details of how altered neuronal activity elicits subcellular redox changes have remained difficult to resolve. Current redox sensitive dyes and fluorescent proteins can quantify spatially distinct changes in reactive oxygen species levels, but multicolor probes are needed to accurately analyze compartment-specific redox dynamics in single cells that can be masked by population averaging. We previously engineered genetically encoded red-shifted redox-sensitive fluorescent protein sensors using a Förster resonance energy transfer relay strategy.

The temporal compression of events during episodic future thinking.

While the cognitive and neural mechanisms that underlie episodic future thinking are increasingly well understood, little is known about how the temporal unfolding of events is represented in future simulations. In this study, we leveraged wearable camera technology to examine whether real-world events are structured and compressed in the same way when imagining the future as when remembering the past. We found that future events were simulated at proportionally higher speed than past events and that the density of experience units representing the unfolding of events was lower for future than for past episodes.