Article
Biochemistry & Molecular Biology
Nicole Balasco, Luciana Esposito, Alfonso De Simone, Luigi Vitagliano
Summary: This study investigated the structural basis of conformational preferences of genetically encoded amino acid residues, revealing that different regions of the Ramachandran plot may exhibit similar or anticorrelated amino acid propensities.
Article
Biochemistry & Molecular Biology
Matic Broz, Marko Jukic, Urban Bren
Summary: Protein structure prediction is a significant challenge in bioinformatics, and this study explores the use of a simple neural network model to predict protein structures. The results show surprising accuracy for predicting phi angles but slightly lower accuracy for predicting psi angles. Additionally, the study demonstrates that simple neural networks can also be used for protein secondary structure prediction.
Article
Biochemical Research Methods
Hong Wei, Boling Wang, Jianyi Yang, Jianzhao Gao
Summary: In this study, a new method called RNAbval was proposed to predict RNA B-factors using random forest and a comprehensive set of features. The method achieved a significant improvement of 9.2-20.5 percent over the state-of-the-art method on two benchmark test datasets. The proposed method is available for access online.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Ashraya Ravikumar, Narayanaswamy Srinivasan
Summary: Proteins undergo various motions that lead to changes in (phi,psi) torsion angles and bond vibrations. This study examines the variations in (phi,psi) values and bond geometry due to vibrational motions in proteins, showing that steric clash-free (phi,psi) space can change continuously during simulations. Minor adjustments to backbone bond geometry allow proteins to access originally inaccessible regions of (phi,psi) space, demonstrating the dynamic nature of steric space in proteins with implications for protein folding.
CURRENT RESEARCH IN STRUCTURAL BIOLOGY
(2021)
Article
Biology
Iain Hunter, Raz Leib
Summary: Natural movement is related to health, but it is difficult to measure. Existing methods cannot capture the full range of natural movement. Comparing movement across different species helps identify common biomechanical and computational principles. Developing a system to quantify movement in freely moving animals in natural environments and relating it to life quality is crucial. This study proposes a theoretical framework based on movement ability and validates it in Drosophila.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Andy Gardner
Summary: Fisher's geometric model is a useful tool for predicting key properties of Darwinian adaptation, and here it is applied to predict differences between the evolution of altruistic versus nonsocial phenotypes. The results suggest that the effect size maximizing probability of fixation is smaller in the context of altruism and larger in the context of nonsocial phenotypes, leading to lower overall probability of fixation for altruism and higher overall probability of fixation for nonsocial phenotypes.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Thomas F. Pak, Joe Pitt-Francis, Ruth E. Baker
Summary: Cell competition is a process where cells interact in multicellular organisms to determine a winner or loser status, with loser cells being eliminated through programmed cell death. The winner cells then populate the tissue. The outcome of cell competition is context-dependent, as the same cell type can win or lose depending on the competing cell type. This paper proposes a mathematical framework to study the emergence of winner or loser status, highlighting the role of active cell death and identifying the factors that drive cell competition in a cell-based modeling context.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Haruto Tomizuka, Yuuya Tachiki
Summary: Batesian mimicry is a strategy in which palatable prey species resemble unpalatable prey species to avoid predation. The evolution of this mimicry plays a crucial role in protecting the unpalatable species from extinction.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Jason W. Olejarz, Martin A. Nowak
Summary: Gene drive technology shows potential for population control, but its release may have unpredictable consequences. The study suggests that the failure of suppression is a natural outcome, and there are complex dynamics among wild populations.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Hamid Ravaee, Mohammad Hossein Manshaei, Mehran Safayani, Javad Salimi Sartakhti
Summary: Gene expression analysis is valuable for cancer classification and phenotype identification. IP3G, based on Generative Adversarial Networks, enhances gene expression data and discovers phenotypes in an unsupervised manner. By converting gene expression profiles into images and utilizing IP3G, new phenotype profiles can be generated, improving classification accuracy.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Beatrix Rahnsch, Leila Taghizadeh
Summary: This study forecasts the evolution of the COVID-19 pandemic in Germany using a network-based inference method and compares it with other approaches. The results show that the network-inference based approach outperforms other methods in short-to mid-term predictions, even with limited information about the new disease. Furthermore, predictions based on the estimation of the reproduction number in Germany can yield more reliable results with increasing data availability, but still cannot surpass the network-inference based algorithm.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Rongsheng Huang, Qiaojun Situ, Jinzhi Lei
Summary: Maintaining tissue homeostasis requires appropriate regulation of stem cell differentiation. Random inheritance of epigenetic states plays a pivotal role in stem cell differentiation. This computational model provides valuable insights into the intricate mechanism governing stem cell differentiation and cell reprogramming, offering a promising path for enhancing the field of regenerative medicine.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Patrick Vincent N. Lubenia, Eduardo R. Mendoza, Angelyn R. Lao
Summary: This study compares insulin signaling in healthy and type 2 diabetes states using reaction network analysis. The results show similarities and differences between the two conditions, providing insights into the mechanisms of insulin resistance, including the involvement of other complexes, less restrictive interplay between species, and loss of concentration robustness in GLUT4.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Nuverah Mohsin, Heiko Enderling, Renee Brady-Nicholls, Mohammad U. Zahid
Summary: Mathematical modeling is crucial in understanding radiobiology and designing treatment approaches in radiotherapy for cancer. This study compares three tumor volume dynamics models and analyzes the implications of model selection. A new metric, the point of maximum reduction of tumor volume (MRV), is introduced to quantify the impact of radiotherapy. The results emphasize the importance of caution in selecting models of response to radiotherapy due to the artifacts imposed by each model.
JOURNAL OF THEORETICAL BIOLOGY
(2024)
Article
Biology
Armindo Salvador
Summary: Michael Savageau's Biochemical Systems Analysis papers have had a significant impact on Systems Biology, generating core concepts and tools. This article provides a brief summary of these papers and discusses the most relevant developments in Biochemical Systems Theory since their publication.
JOURNAL OF THEORETICAL BIOLOGY
(2024)