New Publication from Campbell Lab

(source: Nature Communications) The Campbell lab, led by its Bioinformatics students, has just been published for SCTK-QC, a pipeline for comprehensive QC of single-cell RNA-seq data. This pipeline will help with reprocessing and QC efforts in consortiums. Click here to read the full publication.

Detection of dementia on voice recordings using deep learning: a Framingham Heart Study

(Source: BMC Alzheimer’s Research and Therapy) New publication from Chonghua Xue, Bioinformatics Analyst and Dr. Vijaya Kolachalama, Assistant Professor of Medicine in the Section of Computational Biomedicine. See below for a brief summary and click the link to read the whole article. Background Identification of reliable, affordable, and easy-to-use strategies for detection of dementia is […]

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data

(Source: Oxford Academic) New publication from Dr. Stefano Monti, Associate Professor of Medicine in the Section of Computational Biomedicine. See below for a brief summary and click the link to read the whole article. As high-throughput genomics assays become more efficient and cost effective, their utilization has become standard in large-scale biomedical projects. These studies […]

Subchondral bone length in knee osteoarthritis: A deep learning derived imaging measure and its association with radiographic and clinical outcomes

(Source: Wiley Online Library) New Publication from Dr. Vijaya Kochalama, Assistant Professor of Medicine in the Section of Computational Biomedicine. Please see below for a brief summary and click the link to read the full article. Objective Develop a bone shape measure that reflects the extent of cartilage loss and bone flattening in knee osteoarthritis […]

Animalcules: interactive microbiome analytics and visualization in R

Source: BMC (Part of Springer Nature) New publication from Dr. Evan Johnson, Dr. Stefano Monti, Anthony Federico and collaborators – see below for the abstract and to read more. Background Microbial communities that live in and on the human body play a vital role in health and disease. Recent advances in sequencing technologies have enabled […]

Enhancing magnetic resonance imaging-driven Alzheimer’s disease classification performance using generative adversarial learning

Source: BMC (Part of Springer Nature) New publication from Dr. Vijaya Kolachalama and collaborators – see below for the abstract and to read more. Background Generative adversarial networks (GAN) can produce images of improved quality but their ability to augment image-based classification is not fully explored. We evaluated if a modified GAN can learn from […]

New Publication – Contextualized Protein-Protein Interactions

Source: Patterns Highlights We present PPI Context: contextualization of existing literature-curated PPIs A resource for filtering PPIs by cell-line information mined from reporting studies A fast and flexible pipeline implementing the presented data mining method The Bigger Picture Existing literature-curated protein-protein interaction (PPI) databases usually aggregate cell-type-agnostic interactions, yet PPIs are dependent on environmental conditions. […]