Thomas Dandekar

This study validates an alveolar-like macrophage model as a physiologically relevant in vitro system for studying early Aspergillus fumigatus infection dynamics.

The paper identifies a CDK1-CDKN1A-WEE1 bottleneck in gemcitabine resistance using trajectory-coupled network analysis in PDAC models and patient data.

The paper simulates non-local information processing in associative brain regions using holographic wave patterns and compares results with electrophysiology and EEG data.

The paper shows platelet signaling cascades are complex decision problems solved efficiently using heuristics, leading to fast responses but potential chronic inflammation under stress.

A neural model of non-local information processing on a neocolumnar architecture replicates electrophysiological data from primates, showing high-frequency activity during visual perception.

CoxBase provides an online platform for managing, analyzing, and typing Coxiella burnetii genomic sequences to support epidemiological surveillance.

The paper highlights the importance of accurate metadata in biological data to prevent errors and advocates for improved software and controls to maintain data quality.

The paper identifies positively selected genes in Aspergillus fumigatus and related species, highlighting their roles in virulence, immune evasion, and adaptation.

The paper examines how biological cells make fast, risky decisions that contribute to inflammation and cancer, drawing parallels to computational strategies for solving complex problems.

The paper develops and validates a model of cGMP signaling and VASP phosphorylation in platelets using data-driven approaches and experimental validation.

The paper introduces an automated method to classify synaptic vesicles in C. elegans electron tomograms using machine learning, finding increased DCVs and greater distance from AZs in dauer larvae.