13 papers · ranked by Valyu relevance
Pariksheet Nanda, Maral Budak, Christian T. Michael, Kathryn Krupinsky + 1 more
Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex…
Lionel Kusch, Sandra Diaz, Wouter Klijn, Kim Sontheimer + 3 more
Integration of information across heterogeneous sources creates added scientific value. It is, however, a challenge to progress, often a barrier, to interoperate data, tools and models across spatial and temporal scales. Here we present a design template for coupling simulators operating at different scales and…
Manik Kuchroo, Jessie Huang, Patrick Wong, Jean-Christophe Grenier + 23 more
The biomedical community is producing increasingly high dimensional datasets, integrated from hundreds of patient samples, which current computational techniques struggle to explore. To uncover biological meaning from these complex datasets, we present an approach called Multiscale PHATE, which learns abstracted…
S. Kashif Sadiq, Abraham Muñiz Chicharro, Patrick Friedrich, Rebecca C. Wade
We develop an approach to characterise the effects of gating by a multi-conformation protein consisting of macrostate conformations that are either accessible or inaccessible to ligand binding. We first construct a Markov state model of the apo-protein from atomistic molecular dynamics simulations from which we…
Zhen Zhou, Dhivya Srinivasan, Hongming Li, Ahmed Abdulkadir + 13 more
To learn multiscale functional connectivity patterns of the aging brain, we built a brain age prediction model of functional connectivity measures at seven scales on a large fMRI dataset, consisting of resting-state fMRI scans of 4259 individuals with a wide age range (22 to 97 years, with an average of 63) from five…
Alexander J. Bryer, Juan R. Perilla
Dimensionality reduction via coarse grain modeling has positioned itself as an indispensable tool for decades, particularly for biomolecular simulations where atomic systems encompass hundreds of millions of atoms. While distinct flavors of coarse grain modeling exist, those occupying the coarse end of the spectrum are…
Andrea Tangherloni, Marco S. Nobile, Paolo Cazzaniga, Giulia Capitoli + 4 more
Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can then be tested with targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the…
Lin Chen, Yuhan Chen, Ziqi Cheng, Jing Guo + 20 more
MHPC512 is a massively parallel, special-purpose supercomputer designed primarily for atomic-level molecular dynamics (MD) simulations of biomolecular systems. It comprises 512 processor units interconnected by a high-speed three-dimensional torus network and employs a custom chip architecture that uses 35-bit…
J.R. Porter, M.I. Zimmerman, G.R. Bowman
Markov state models (MSMs) are quantitative models of protein dynamics that are useful for uncovering the structural fluctuations that proteins undergo, as well as the mechanisms of these conformational changes. Given the enormity of conformational space, there has been ongoing interest in identifying a small number of…
Maxim Lippeveld, Daniel Peralta, Andrew Filby, Yvan Saeys
Due to high resolution and throughput of modern image cytometry platforms, morphologically profiling generated datasets poses a significant computational challenge. Here, we present Scalable Cytometry Image Processing (SCIP), an image processing software aimed at running on distributed high performance computing…
Parashar Dhapola, Johan Rodhe, Rasmus Olofzon, Thomas Bonald + 3 more
The increasing capacity to perform large-scale single-cell genomic experiments continues to outpace the computational requirements to efficiently handle growing datasets. Herein we present Scarf, a modularly designed Python package that seamlessly interoperates with other single-cell toolkits and allows for…
Curtis Goolsby, Ashkan Fakharzadeh, Mahmoud Moradi
We have formulated a Riemannian framework for describing the geometry of collective variable spaces of biomolecules within the context of collective variable based molecular dynamics simulations. The formalism provides a theoretical framework to develop enhanced sampling techniques, path-finding algorithms, and…
Esley Torres García, Raúl Pinto Cámara, Alejandro Linares, Damián Martínez + 22 more
Mean-Shift Super Resolution (MSSR) is a principle based on the Mean Shift theory that improves the spatial resolution in fluorescence images beyond the diffraction limit. MSSR works on low- and high-density fluorophore images, is not limited by the architecture of the detector (EM-CCD, sCMOS, or photomultiplier-based…