At first glance, biology and computer science are diametrically opposed sciences. Biology deals with carbon based life forms shaped by evolution and natural selection. Computer Science deals with electronic machines designed by engineers and guided by mathematical algorithms. In this brief paper, we review biologically inspired computing. We discuss several models of computation which have arisen from various biological studies. We show what these have in common, and conjecture how biology can still suggest answers and models for the next generation of computing problems. We discuss computation and argue that these biologically inspired models do not extend the theoretical limits on computation. We suggest that, in practice, biological models may give more succinct representations of various problems, and we mention a few cases in which biological models have proved useful. We also discuss the reciprocal impact of computer science on biology and cite a few significant contributions to biological science.
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http://dx.doi.org/10.1016/j.biosystems.2012.12.005 | DOI Listing |
Stat Med
February 2025
Department of Mathematical Sciences, University of Texas at Dallas, Richardson, Texas, USA.
Multi-gene panel testing allows efficient detection of pathogenic variants in cancer susceptibility genes including moderate-risk genes such as ATM and PALB2. A growing number of studies examine the risk of breast cancer (BC) conferred by pathogenic variants of these genes. A meta-analysis combining the reported risk estimates can provide an overall estimate of age-specific risk of developing BC, that is, penetrance for a gene.
View Article and Find Full Text PDFProtein Sci
February 2025
Department of Physics, University of Washington, Seattle, Washington, USA.
Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, 611002, Tamil Nadu, India.
In response to the pressing need for the detection of Monkeypox caused by the Monkeypox virus (MPXV), this study introduces the Enhanced Spatial-Awareness Capsule Network (ESACN), a Capsule Network architecture designed for the precise multi-class classification of dermatological images. Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. CapsNets' inherent ability to recognize and process crucial spatial relationships within images outperforms conventional CNNs, particularly in tasks that require the distinction of visually similar classes.
View Article and Find Full Text PDFPediatr Nephrol
January 2025
CERTAIN Research Network, Heidelberg, Germany.
Background: We investigated factors associated with post-transplant growth in pediatric kidney transplant (KTx) recipients with a focus on plasma bicarbonate (HCO3) and estimated the effect of alkali treatment on growth.
Methods: In this study of the CERTAIN Registry, data were collected up to 5 years post-transplant. Generalized Additive Mixed Models were applied to assess the association between post-transplant growth and covariates.
Sci Rep
January 2025
Department of Computer Science and Engineering, Engineering College Ajmer, Ajmer, Rajasthan, India.
To combat dynamically loaded code in anti-emulated environments, DLCDroid is an Android app analysis framework. DL-CDroid uses the reflection API to effectively identify information leaks due to dynamically loaded code within malicious apps, incorporating static and dynamic analysis techniques. The Dynamically Loaded Code (DLC) technique employs Java features to allow Android apps to dynamically expand their functionality at runtime.
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