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The relationship between interactions, flexibility and disorder in proteins has been explored from many angles: folding upon binding, flexibility of the core relative to the periphery, entropy changes, etc. In this work, we provide…
Large-scale simultaneous mRNA translation and the resulting competition for the available ribosomes has important implications to the cell's functioning and evolution. Developing a better understanding of the intricate correlations between…
Protein language models have excelled in a variety of tasks, ranging from structure prediction to protein engineering. However, proteins are highly diverse in functions and structures, and current state-of-the-art models including the…
Drug resistance is a major threat to the global health and a significant concern throughout the clinical treatment of diseases and drug development. The mutation in proteins that is related to drug binding is a common cause for adaptive…
Deep Learning can significantly benefit cancer proteomics and genomics. In this study, we attempt to determine a set of critical proteins that are associated with the FLT3-ITD mutation in newly-diagnosed acute myeloid leukemia patients. A…
Co-optimizing mRNA sequences for both codon optimality and secondary structure is crucial for producing stable and efficacious mRNA therapeutics. Codon optimization, which adjusts nucleotide sequences to enhance translational efficiency,…
High-dimensional tensor models are notoriously computationally expensive to train. We present a meta-learning algorithm, MMT, that can significantly speed up the process for spatial tensor models. MMT leverages the property that spatial…
Here we study how mutations which change physical properties of cell proteins (stability) impact population survival and growth. In our model the genotype is presented as a set of N numbers, folding free energies of cells N proteins.…
Deployment of Deep Neural Networks in medical imaging is hindered by distribution shift between training data and data processed after deployment, causing performance degradation. Post-Deployment Adaptation (PDA) addresses this by tailoring…
Recent state-of-the-art language models utilize a two-phase training procedure comprised of (i) unsupervised pre-training on unlabeled text, and (ii) fine-tuning for a specific supervised task. More recently, many studies have been focused…
Small interfering RNA (siRNA) is a short double-stranded RNA molecule (about 21-23 nucleotides) with the potential to cure diseases by silencing the function of target genes. Due to its well-understood mechanism, many siRNA-based drugs have…
Gene regulation in higher eukaryotes involves a complex interplay between the gene proximal promoter and distal genomic elements (such as enhancers) which work in concert to drive spatio-temporal expression. The experimental…
Background: Recent developments have made it possible to accelerate neural networks training significantly using large batch sizes and data parallelism. Training in an asynchronous fashion, where delay occurs, can make training even more…
The functional diversity in factors identified in association with non-alcoholic fatty liver disease (NAFLD) necessitates the utilization of holistic approaches to investigate the network properties of NAFLD pathogenesis. We describe the…
Background: MicroRNAs (miRNAs) play multiple roles in tumor biology [1]. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration [2]. Specifically, computational…
Positron emission tomography (PET) scans expose patients to radiation, which can be mitigated by reducing the dose, albeit at the cost of diminished quality. This makes low-dose (LD) PET recovery an active research area. Previous studies…
The ac4C modification on mRNA has been demonstrated to be associated with various diseases; however, its molecular mechanism remains unclear. The wet lab experiments produced relatively rough data, which lack precise ac4C modification…
Integrating biological information from different sources to understand cellular processes is an important problem in systems biology. We use data from mRNA expression arrays and chemical kinetics to formulate a metabolic model relevant to…
We propose a multiscale mechanobiological model of bone remodelling to investigate the site-specific evolution of bone volume fraction across the midshaft of a femur. The model includes hormonal regulation and biochemical coupling of bone…
Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels due to impaired insulin production or function. Two main forms are recognized: type 1 diabetes (T1D), which involves autoimmune destruction of…