Research Insights
The Research Insights area highlights recent advances in science and medicine as well as global laboratory research. Our readers gain tremendous benefit from research discoveries in an indirect manner.
TORC1 Regulation of Dendrite Regrowth After Pruning is Linked to Actin and Exocytosis
Neurite pruning and regrowth are important mechanisms to adapt neural circuits to distinct developmental stages
Integration of a Multi-omics Stem Cell Differentiation Dataset Using a Dynamical Model
Stem cell differentiation is a highly dynamic process involving pervasive changes in gene expression The large majority of existing studies has characterized differentiation at the level of individual molecular profiles such as the transcriptome or the proteome
CRISPR-Cas Effector Specificity and Cleavage Site Determine Phage Escape Outcomes
CRISPRmediated interference relies on complementarity between a guiding CRISPR RNA crRNA and target nucleic acids to provide defense against bacteriophage
Characterization of GSDME in Amphioxus Provides Insights Into the Functional Evolution of GSDM-mediated Pyroptosis
Members of the gasdermin GSDM family are poreforming effectors that cause membrane permeabilization and pyroptosis a lytic proinflammatory type of cell death
Myosina is a Druggable Target in the Widespread Protozoan Parasite Toxoplasma Gondii
Toxoplasma gondiiis a widespread apicomplexan parasite that can cause severe disease in its human hosts
CRISPR-Analytics (CRISPR-A): A platform for precise analytics and simulations for gene editing
Gene editing characterization with currently available tools does not always give precise relative proportions among the different types of gene edits present in an edited bulk of cells
New Workflow Predicts Drug Targets Against Sars-Cov-2 via Metabolic Changes in Infected Cells
COVID is one of the deadliest respiratory diseases and its emergence caught the pharmaceutical industry off guard While vaccines have been rapidly developed treatment options for infected people remain scarce and COVID poses a substantial global threat This study presents a novel workflow to predict robust druggable targets against emerging RNA vir...
A Systematic Evaluation of Deep Learning Methods for the Prediction of Drug Synergy in Cancer
One of the main obstacles to the successful treatment of cancer is the phenomenon of drug resistance A common strategy to overcome resistance is the use of combination therapies However the space of possibilities is huge and efficient search strategies are required Machine Learning ML can be a useful tool for the discovery of novel
Spatial and Temporal Correlations in Human Cortex Are Inherently Linked and Predicted by Functional Hierarchy, Vigilance State as Well as Antiepileptic Drug Load
The ability of neural circuits to integrate information over time and across different cortical areas is believed an essential ingredient for information processing in the brain Temporal and spatial correlations in cortex dynamics have independently been shown to capture these integration properties in taskdependent ways A fundamental question rema...
scAmpi—A versatile pipeline for single-cell RNA-seq analysis from basics to clinics
Singlecell RNA sequencing scRNAseq has emerged as a powerful technique to decipher tissue composition at the singlecell level and to inform on disease mechanisms tumor heterogeneity and the state of the immune microenvironment Although multiple methods for the computational analysis of scRNAseq data exist their application in a clinical setting dem...
