Publications by authors named "Jessica B Wagenknecht"
Article Synopsis
- AI deep learning methods are transforming the way scientists understand and predict protein structures, allowing for innovative approaches to tackle complex biological questions.
- Recent analysis of 2878 proteins revealed that while AI predictions, specifically from AlphaFold v2, are highly accurate for many folds, a significant percentage show discrepancies in conformations, emphasizing the importance of cautious interpretation of these predictions.
- The study highlights that proteins with high conformational variability are crucial for key biological functions, suggesting that current prediction models may overlook essential aspects of protein flexibility.
Interpreting genetic changes observed in individual patients is a critical challenge. The array of immune deficiency syndromes is typically caused by genetic variation unique to individuals. Therefore, new approaches are needed to interpret functional variation and accelerate genomics interpretation.
View Article and Find Full Text PDFCurrent capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions.
View Article and Find Full Text PDFCurrent capabilities in genomic sequencing outpace functional interpretations. Our previous work showed that 3D protein structure calculations enhance mechanistic understanding of genetic variation in sequenced tumors and patients with rare diseases. The KRAS GTPase is among the critical genetic factors driving cancer and germline conditions.
View Article and Find Full Text PDF