Article
Chemistry, Physical
Anirban Ghosh, Sudipta Mandal, Dipanjan Chakraborty
Summary: This paper investigates the persistence probability of an active Brownian particle with shape asymmetry, extending the study to an active anisotropic particle. The analytical expression is validated against numerical simulations and the method proposed is tested to distinguish between active and passive anisotropic particles.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Md Ramiz Raza, Jijo Easo George, Savita Kumari, Mithun K. Mitra, Debjani Paul
Summary: We present a two-layer microfluidic device to examine how confinement and chemical gradient affect the motility of E. coli. Our results indicate that the trajectories of bacteria exhibit superdiffusive behavior even without a chemical gradient. This behavior is further enhanced when a chemical gradient or stronger confinement is introduced. Our findings suggest that E. coli modulates both its runs and tumbles in response to physical confinement and chemical gradients. Understanding bacteria's motility behavior in their natural habitats has implications for various applications.
Article
Cell Biology
Felix Ellett, Anika L. Marand, Daniel Irimia
Summary: This article investigates the integration of multiple chemical signals and directional decisions in neutrophil chemotaxis, and presents a series of experiments using microfluidic designs to test the sensitivity of chemotaxing neutrophils to various perturbations. The data support a model of biased random walk for neutrophil chemotaxis.
JOURNAL OF LEUKOCYTE BIOLOGY
(2022)
Article
Multidisciplinary Sciences
M. Smerlak
Summary: This paper explores the link between selection for mutational robustness and the navigability of neutral networks, showing that sequences of neutral mutations follow a maximal entropy random walk. The study also revisits a word-game model of evolution, finding that the likelihood of certain substitution sequences can decrease with population size. These counterintuitive results highlight the intersection of evolutionary dynamics, information theory, and physics.
Article
Computer Science, Artificial Intelligence
Christian Toth, Denis Helic, Bernhard C. Geiger
Summary: This paper presents Synwalk, a random walk-based community detection method, which detects communities in networks by synthesizing random walks. The results indicate that Synwalk performs robustly in various network scenarios.
DATA MINING AND KNOWLEDGE DISCOVERY
(2022)
Article
Biology
D. A. Ahmed, S. Benhamou, M. B. Bonsall, S. Petrovskii
Summary: The study investigates the impact of 3D random walks and trap shapes on trapping efficiency. Results reveal that trap counts are influenced by trap shape and size, leading to a better understanding of trap count interpretations.
JOURNAL OF THEORETICAL BIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Alister Burt, C. Keith Cassidy, Phillip J. Stansfeld, Irina Gutsche
Summary: This study utilized cryo-electron tomography to visualize the native-state chemosensory arrays in E. coli minicells, revealing a new p2-symmetric array architecture that differs from the previously described p6-symmetric architecture. The researchers proposed molecular models for this alternative architecture and the canonical p6-symmetric assembly, evaluating the functional implications and potential effects for future studies based on the observed data.
Article
Multidisciplinary Sciences
Henrik Seckler, Ralf Metzler
Summary: Machine-learning techniques are used to decode anomalous-diffusion data and provide both predicted output and uncertainty estimates.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
S. T. Johnston, K. J. Painter
Summary: Collective migration involves interpreting navigational cues and perceiving other individuals, with communication reducing orientation errors. A mathematical model shows that collective navigation is more efficient than individual navigation, especially in low-information environments. In navigation blindspots, connections between individuals in information-rich and information-poor areas enhance navigation efficiency.
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2021)
Article
Mathematics, Applied
Jiri Cerny
Summary: This study considers the zero-average Gaussian free field on finite d-regular graphs with fixed d (greater than or equal to 3). This class includes d-regular expanders of large girth and typical realisations of random d-regular graphs. The study shows that the level set of the zero-average Gaussian free field above level h has a giant component in the whole supercritical phase.
COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS
(2023)
Article
Engineering, Environmental
Hassan Elagami, Sven Frei, Gabriele Trommer, Benjamin S. Gilfedder
Summary: In this study, a series of microplastic addition experiments were conducted in a 12 x 3 m lake mesocosm, and the transport of microplastics through the lake water column was traced. The results showed that the residence time in the water column largely depended on particle size and lake hydrodynamics. However, the smallest particles were not well represented by the model, indicating the complexity of microplastic transport within lakes.
Article
Physics, Fluids & Plasmas
Zhenqi Lu, Johan Wahlstrom, Arye Nehorai
Summary: The study focuses on spreading phenomena in networks, especially disease transmission, and proposes a method to effectively contain and suppress epidemic outbreaks through a combination of antidote distribution and partial quarantine. By improving existing antidote distribution schemes based on personalized PageRank, the study shows that the probability of infection spreading to the whole network is bounded, and the infection inside the subnetwork will disappear after a period proportional to the logarithm of the initially infected nodes. The strategy is dependent only on infection rate, recovery rate, and the topology around initially infected nodes, regardless of the rest of the network.
Article
Mathematics
Paula Cadavid, Mary Luz Rodino Montoya, Pablo M. Rodriguez
Summary: Evolution algebras are non-associative algebras inspired by biological phenomena, with various applications and connections in different mathematical fields. This work discusses the relationship between evolution algebras associated with a given graph, revealing that both algebras are strongly isotopic for any graph, with their isomorphism depending on specific conditions. The study provides new insights into the interplay between evolution algebras and graphs, addressing open problems and offering conjectures supported by examples and partial results.
LINEAR & MULTILINEAR ALGEBRA
(2021)
Article
Physics, Fluids & Plasmas
Henrik Christiansen, Suman Majumder, Wolfhard Janke
Summary: The study focuses on the nonequilibrium dynamics of the nonconserved Ising model with power-law decaying long-range interactions in two spatial dimensions at zero temperature. They found that the growth exponent is independent of the parameter sigma and the fractal dimension only recovers to the value of the nearest-neighbor Ising model in the large interaction region.
Article
Genetics & Heredity
Johana F. Castro, Diethard Tautz
Summary: The study explores the potential for de novo gene evolution from random nucleotide sequences using E. coli peptide libraries. Shorter peptides are more likely to increase cell growth frequency, while longer peptides are more likely to decrease it. The data indicate that random sequences can be a source of evolutionary innovation, with some sequences providing growth advantage or being well tolerated by cells.
Article
Biochemical Research Methods
J. Hajne, K. L. Hanson, H. van Zalinge, D. V. Nicolau
IEEE TRANSACTIONS ON NANOBIOSCIENCE
(2015)
Article
Chemistry, Physical
Myhuong T. Nguyen, Alan L. Chaffee, Reinhard I. Boysen, Dan V. Nicolau, Milton T. W. Hearn
MOLECULAR SIMULATION
(2016)
Article
Engineering, Biomedical
Luisa Filipponi, Peter Livingston, Ondrej Kaspar, Viola Tokarova, Dan V. Nicolau
BIOMEDICAL MICRODEVICES
(2016)
Article
Biochemical Research Methods
Elitsa Asenova, Hsin-Yu Lin, Eileen Fu, Dan V. Nicolau, Dan V. Nicolau
IEEE TRANSACTIONS ON NANOBIOSCIENCE
(2016)
Review
Chemistry, Analytical
Reinhard I. Boysen, Lachlan J. Schwarz, Dan V. Nicolau, Milton T. W. Hearn
JOURNAL OF SEPARATION SCIENCE
(2017)
Article
Biochemical Research Methods
Ondrej Kaspar, Hailong Zhang, Viola Tokarova, Reinhard I. Boysen, Gemma Rius Sune, Xavier Borrise, Francesco Perez-Murano, Milton T. W. Hearn, Dan V. Nicolau
Article
Multidisciplinary Sciences
Dan V. Nicolau, Mercy Lard, Till Korten, Falco C. M. J. M. van Delftf, Malin Persson, Elina Bengtsson, Alf Mansson, Stefan Diez, Heiner Linke, Dan V. Nicolau
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2016)
Article
Biophysics
S. Dobroiu, F. C. M. J. M. van Delft, J. Aveyard-Hanson, Prasad Shetty, D. V. Nicolau
BIOSENSORS & BIOELECTRONICS
(2019)
Article
Biophysics
Kathryn F. A. Clancy, Sebastien Dery, Veronique Laforte, Prasad Shetty, David Juncker, Dan V. Nicolau
BIOSENSORS & BIOELECTRONICS
(2019)
Review
Biology
Falco C. M. J. M. van Delft, Giulia Ipolitti, Dan V. Nicolau, Ayyappasamy Sudalaiyadum Perumal, Ondrej Kasper, Sara Kheireddine, Sebastian Wachsmann-Hogiu, Dan V. Nicolau
Article
Multidisciplinary Sciences
Marie Held, Ondrej Kaspar, Clive Edwards, Dan V. Nicolau
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2019)
Article
Physics, Multidisciplinary
Falco C. M. J. M. van Delft, Ayyappasamy Sudalaiyadum Perumal, Anja van Langen-Suurling, Charles de Boer, Ondrej Kaspar, Viola Tokarova, Frank W. A. Dirne, Dan Nicolau
Summary: Research suggests that protein-driven molecular motors in cytoskeletal filaments and autonomously moving bacteria can serve as computational paradigms and alternatives for solving small-scale NP-complete problems. Before scaling up to large computational networks, it is necessary to characterize bacterial motility in various geometrical structures and optimize the stochastic traffic splitting in computational device junctions.
NEW JOURNAL OF PHYSICS
(2021)
Article
Physics, Multidisciplinary
Ayyappasamy Sudalaiyadum Perumal, Zihao Wang, Giulia Ippoliti, Falco C. M. J. M. van Delft, Lila Kari, Dan Nicolau
Summary: Existing algorithms for solving NP-complete problems face limitations in practical application due to the exponential growth in solution space, leading to alternative massively parallel computing approaches such as DNA computing and network biocomputing with agents. While these alternatives show promise in certain performance criteria compared to electronic computing, they each have their own limitations in terms of volume, computing time, and energy efficiency, suggesting the need for breakthroughs or hybrid computing approaches to overcome these challenges.
NEW JOURNAL OF PHYSICS
(2021)
Article
Biochemical Research Methods
Sara Kheireddine, Ayyappasamy Sudalaiyadum Perumal, Zachary J. Smith, Dan V. Nicolau, Sebastian Wachsmann-Hogiu
Article
Biophysics
Kristi L. Hanson, Florin Fulga, Serban Dobroiu, Gerardin Solana, Ondrej Kaspar, Viola Tokarova, Dan V. Nicolau
BIOSENSORS & BIOELECTRONICS
(2017)
Article
Biology
Kunal Bhattacharya, Shikha Mahato, Satyendra Deka, Nongmaithem Randhoni Chanu, Amit Kumar Shrivastava, Pukar Khanal
Summary: Chemoresistance, a major challenge in cancer treatment, is associated with the cellular glutathione-related detoxification system. A study has identified GSTP1 enzyme as critical in the inactivation of anticancer drugs and suggests the need for GSTP1 inhibitors to combat chemoresistance. Through molecular docking and simulations, the study found that quercetin 7-O-beta-D-glucoside showed promise as a potential candidate for addressing chemoresistance in cancer patients.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)
Article
Biology
Manwi Shankar, Majji Sai Sudha Rani, Priyanka Gopi, P. Arsha, Prateek Pandya
Summary: This study investigates the interaction between the food dye BBY and the serum protein BSA. The results show that BBY binds to a specific site on BSA through hydrophobic interactions, affecting the structural stability of the protein. These findings enhance our understanding of the molecular-level interactions between BBY and BSA.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)
Article
Biology
Chi Zhang, Qian Gao, Ming Li, Tianfei Yu
Summary: In this study, we propose a graph neural network-based autoencoder model, AGraphSAGE, that effectively predicts protein-protein interactions across diverse biological species by integrating gene ontology.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)
Article
Biology
Kangjie Wu, Liqian Xu, Xinxiang Li, Youhua Zhang, Zhenyu Yue, Yujia Gao, Yiqiong Chen
Summary: Named Entity Recognition (NER) is a crucial task in natural language processing (NLP) and big data analysis, with wide application range. This paper proposes an improved neural network method for NER of rice genes and phenotypes, which can learn semantic information in the context without feature engineering. Experimental results show that the proposed model outperforms other models.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)
Article
Biology
Suman Hait, Sudip Kundu
Summary: Interactions between amino acids in proteins are crucial for stability and structural integrity. Thermophiles have more and more stable interactions to survive in extreme environments. Different types of interactions are enriched in different structural regions.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)
Article
Biology
Kountay Dwivedi, Ankit Rajpal, Sheetal Rajpal, Virendra Kumar, Manoj Agarwal, Naveen Kumar
Summary: This study aims to identify biomarkers for non-small cell lung cancer (NSCLC) using copy number variation (CNV) data. A novel deep learning architecture, XL1R-Net, is proposed to improve the classification accuracy for NSCLC subtyping. Twenty NSCLC-relevant biomarkers are uncovered using explainable AI (XAI)-based feature identification. The results show that the identified biomarkers have high classification performance and clinical relevance. Additionally, twelve of the biomarkers are potentially druggable and eighteen of them have a high probability of predicting NSCLC patients' survival likelihood according to the Drug-Gene Interaction Database and the K-M Plotter tool, respectively. This research suggests that investigating these seven novel biomarkers can contribute to NSCLC therapy, and the integration of multiomics data and other sources will help better understand NSCLC heterogeneity.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)
Article
Biology
Pengli Lu, Wenqi Zhang, Jinkai Wu
Summary: Researchers have developed a computational method, AMPCDA, to predict circRNA-disease associations using predefined metapaths, achieving high predictive accuracy. This method effectively combines node embeddings with higher-order neighborhood representations and provides valuable guidance for revealing new disease mechanisms in biological research.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2024)