Discovering Molecular Targets in Cancer with Multiscale Modeling.

Drug Dev Res

Harvard-MIT (HST) Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA.

Published: February 2011

Multiscale modeling is increasingly being recognized as a promising research area in computational cancer systems biology. Here, exemplified by two pioneering studies, we attempt to explain why and how such a multiscale approach paired with an innovative cross-scale analytical technique can be useful in identifying high-value molecular therapeutic targets. This novel, integrated approach has the potential to offer a more effective in silico framework for target discovery and represents an important technical step towards systems medicine.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3092304PMC
http://dx.doi.org/10.1002/ddr.20401DOI Listing

Publication Analysis

Top Keywords

multiscale modeling
8
discovering molecular
4
molecular targets
4
targets cancer
4
cancer multiscale
4
modeling multiscale
4
modeling increasingly
4
increasingly recognized
4
recognized promising
4
promising area
4

Similar Publications

Cellular forces regulate an untold spectrum of living processes, such as cell migration, gene expression, and ion conduction. However, a quantitative description of mechanical control remains elusive due to the lack of general, live-cell tools to measure discrete forces between biomolecules. Here we introduce a computational pipeline for force measurement that leverages well-defined, tunable release of a mechanically activated small molecule fluorophore.

View Article and Find Full Text PDF

Expediated modeling of burn events results (EMBER): A screening-level dataset of 2023 ozone fire impacts in the US.

Data Brief

February 2025

Office of Air and Radiation, US Environmental Protection Agency, 109 TW Alexander Dr, PO Box 12055, RTP, NC 27711, USA.

The Expedited Modeling of Burn Events Results (EMBER) dataset consists of 36-km grid-spacing Community Multiscale Air Quality (CMAQ) photochemical modeling for the summer of 2023. For emissions, these simulations utilized representative monthly and day-of-week anthropogenic emissions from a recent year and preliminary day-specific 2023 fire emissions derived using BlueSky pipeline. The base model run simulated ozone concentrations across the contiguous US during Apr 11-Sep 29, 2023.

View Article and Find Full Text PDF

Research on bearing fault diagnosis based on a multimodal method.

Math Biosci Eng

December 2024

School of Information Engineering, Nantong Institute of Technology, Nantong 226002, Jiangsu, China.

As an essential component of mechanical systems, bearing fault diagnosis is crucial to ensure the safe operation of the equipment. However, vibration data from bearings often exhibit non-stationary and nonlinear features, which complicates fault diagnosis. To address this challenge, this paper introduces a novel multi-scale time-frequency and statistical features fusion model (MTSF-FM).

View Article and Find Full Text PDF

The rapid development of flexible electronics necessitates simplified processes that integrate heterogeneous materials and structures. In this study, laser engraving is combined with electrochemical deposition (ECD) to directly fabricate various micro/nano-structured components and flexible electronic circuits. A theoretical framework and simulation model are developed to design the on-demand ECD on laser induced graphene (LIG), enabling the generation of multi-scale copper (Cu) materials with controllable oxidation states.

View Article and Find Full Text PDF

Toward efficient slide-level grading of liver biopsy via explainable deep learning framework.

Med Biol Eng Comput

January 2025

Pathology Department, Beijing Youan Hospital, Capital Medical University, Beijing, 100000, China.

In the context of chronic liver diseases, where variability in progression necessitates early and precise diagnosis, this study addresses the limitations of traditional histological analysis and the shortcomings of existing deep learning approaches. A novel patch-level classification model employing multi-scale feature extraction and fusion was developed to enhance the grading accuracy and interpretability of liver biopsies, analyzing 1322 cases across various staining methods. The study also introduces a slide-level aggregation framework, comparing different diagnostic models, to efficiently integrate local histological information.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!