The early dodder gets the host: decoding the coiling patterns of Cuscuta campestris with automated image processing.

We developed an in-house Python-based image analysis pipeline to investigate the movement patterns of Cuscuta. Our analysis unveiled that the coiling and circumnutation movements of Cuscuta are regulated by its intrinsic circadian rhythm. Cuscuta spp.

Genomics data analysis via spectral shape and topology.

Mapper, a topological algorithm, is frequently used as an exploratory tool to build a graphical representation of data. This representation can help to gain a better understanding of the intrinsic shape of high-dimensional genomic data and to retain information that may be lost using standard dimension-reduction algorithms. We propose a novel workflow to process and analyze RNA-seq data from tumor and healthy subjects integrating Mapper, differential gene expression, and spectral shape analysis.

A critical analysis of plant science literature reveals ongoing inequities.

The field of plant science has grown dramatically in the past two decades, but global disparities and systemic inequalities persist. Here, we analyzed ~300,000 papers published over the past two decades to quantify disparities across nations, genders, and taxonomy in the plant science literature. Our analyses reveal striking geographical biases-affluent nations dominate the publishing landscape and vast areas of the globe have virtually no footprint in the literature.

The shape of things to come: Topological data analysis and biology, from molecules to organisms.

Shape is data and data is shape. Biologists are accustomed to thinking about how the shape of biomolecules, cells, tissues, and organisms arise from the effects of genetics, development, and the environment. Less often do we consider that data itself has shape and structure, or that it is possible to measure the shape of data and analyze it.