Browse Articles

The impact of genetic analysis on the early detection of colorectal cancer

Agrawal et al. | Aug 24, 2023

The impact of genetic analysis on the early detection of colorectal cancer

Although the 5-year survival rate for colorectal cancer is below 10%, it increases to greater than 90% if it is diagnosed early. We hypothesized from our research that analyzing non-synonymous single nucleotide variants (SNVs) in a patient's exome sequence would be an indicator for high genetic risk of developing colorectal cancer.

Read More...

Creating a drought prediction model using convolutional neural networks

Bora et al. | Oct 08, 2024

Creating a drought prediction model using convolutional neural networks
Image credit: The authors

Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.

Read More...

A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Vangal et al. | Sep 28, 2020

A Quantitative Assessment of Time, Frequency, and Time-frequency Algorithms for Automated Seizure Detection and Monitoring

Each year, over 100,000 patients die from Sudden Unexpected Death in Epilepsy (SUDEP). A reliable seizure warning system can help patients stay safe. This work presents a comprehensive, comparative analysis of three different signal processing algorithms for automated seizure/ictal detection. The experimental results show that the proposed methods can be effective for accurate automated seizure detection and monitoring in clinical care.

Read More...

Using DNA Barcodes to Evaluate Ecosystem Health in the SWRCMS Reserve

Horton et al. | Sep 27, 2018

Using DNA Barcodes to Evaluate Ecosystem Health in the SWRCMS Reserve

Although the United States maintains millions of square kilometers of nature reserves to protect the biodiversity of the specimens living there, little is known about how confining these species within designated protected lands influences the genetic variation required for a healthy population. In this study, the authors sequenced genetic barcodes of insects from a recently established nature reserve, the Southwestern Riverside County Multi-Species Reserve (SWRCMSR), and a non-protected area, the Mt. San Jacinto College (MSJC) Menifee campus, to compare the genetic variation between the two populations. Their results demonstrated that the midge fly population from the SWRCMSR had fewer unique DNA barcode sequence changes than the MSJC population, indicating that the comparatively younger nature reserve's population had likely not yet established its own unique genetic drift changes.

Read More...