Like a game of Wheel of Fortune, where you have to fill in missing letters to guess the hidden phrase, analyzing data sometimes requires estimating missing data points by relying on available information in order to get the full picture of what’s being studied.
Daifeng Wang
Daifeng Wang, PhD – Slide of the Week
Our machine-learning framework, brain and organoid manifold alignment (BOMA), first performs a global alignment of developmental gene expression data between brains and organoids.
New Machine Learning Tool Helps Researchers Demonstrate Effectiveness of Stem Cell Based Models
Today, many researchers are using brain organoids – miniaturized and simplified versions of organs produced in a dish typically from stem cells – as analogs for studying the development of the human brain.
Four Waisman investigators receive prestigious Simons Foundation award to study autism
Four Waisman Center investigators will dig deeper into the function of genes implicated in autism and brain development with support from the prestigious Simons Foundation 2022 Pilot Award.
Stem cell project to create new model to study brain development and Down syndrome
Waisman Center researchers are creating a new approach to study how changes to brain development in the womb result in intellectual disability in people with Down syndrome.
A new computational pipeline connects disease and discovery at the cellular level
Could Alzheimer’s disease and schizophrenia be biologically connected?
Daifeng Wang, PhD – Slide of the Week
Understanding cell-type-specific gene regulatory mechanisms from genetic variants to diseases remains challenging. To address this, we developed a computational pipeline, scGRNom (single-cell Gene Regulatory Network prediction from multi-omics), to predict cell-type disease genes and regulatory networks including transcription factors and regulatory elements.
Daifeng Wang, PhD – Slide of the Week
The molecular mechanisms and functions in complex biological systems currently remain elusive. Recent high-throughput techniques, such as next-generation sequencing, have generated a wide variety of multiomics datasets that enable the identification of biological functions and mechanisms via multiple facets. However, integrating these large-scale multiomics data and discovering functional insights are, nevertheless, challenging tasks.
Running toward renewal: new study links physical activity with cognitive health
Research has shown voluntary running is an activity most commonly associated with the reversal of negative impacts of aging and neurodegeneration, but little is understood about why that is.
New researcher uses machine learning to decode genomic information
Recent advances in genome sciences — the study of an organism’s complete set of DNA — present a golden opportunity to identify the genetic causes and underlying mechanisms of intellectual and developmental disabilities. These discoveries …