Article
Physics, Multidisciplinary
Chen Zhou, Haiyan Guo, Shujuan Cao
Summary: A gene network associated with Alzheimer's disease is constructed from multiple data sources, divided into modules and evaluated using different methods. Functional modules are identified through enrichment analysis, and essential genes are predicted using network topology properties and a logical regression algorithm under a Bayesian framework. Based on network pharmacology, potential herbs and herb compounds for AD are selected through visualization and enrichment analysis.
Article
Engineering, Multidisciplinary
Xiangmao Meng, Wenkai Li, Ju Xiang, Hayat Dino Bedru, Wenkang Wang, Fang-Xiang Wu, Min Li
Summary: This study reexamines the essentiality of hub proteins in PPI networks by constructing temporal-spatial dynamic PPI networks and integrating gene expression data and subcellular localization information. The results show that integrating multiple data sources can improve the identification accuracy of essential proteins.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Biochemistry & Molecular Biology
Yajunzi Wang, Jing Li, Daiyun Huang, Yang Hao, Bo Li, Kai Wang, Boya Chen, Ting Li, Xin Liu
Summary: The development of high-throughput omics technologies allows for the quantification of genes and gene products, and pathway enrichment analysis (PEA) provides a solution for extracting biological insights. Topology-based pathway analysis (TPA) methods utilize pathway topology and gene expression data to explore causal relationships. In this study, different BN reconstruction strategies were compared, and results showed varying pathway rankings due to different cyclic structure removal strategies. These findings offer a reference for selecting appropriate methods for data analysis tasks.
Article
Microbiology
Lun Hu, Xiaojuan Wang, Yu-An Huang, Pengwei Hu, Zhu-Hong You
Summary: Proteins play a crucial role in carrying out various physiological functions in cells through interactions, making the prediction of protein-protein interactions essential for understanding biological processes. Computational prediction algorithms have become popular due to the time-consuming and labor-intensive nature of laboratory-based experiments. This study introduces a novel algorithm based on prior information and biological data to accurately predict PPIs.
FRONTIERS IN MICROBIOLOGY
(2021)
Article
Plant Sciences
Dario Di Silvestre, Gianpiero Vigani, Pierluigi Mauri, Sereen Hammadi, Piero Morandini, Irene Murgia
Summary: Network analysis, based on graph theory, is a systems biology approach used to study protein-protein interactions and co-expression networks. This method can assist in identifying novel players involved in multiple homeostatic interactions.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Genetics & Heredity
Dipanka Tanu Sarmah, Sunil Gujjar, Santosh Mathapati, Nandadulal Bairagi, Samrat Chatterjee
Summary: Diabetic retinopathy (DR) is a common complication of diabetes and a leading cause of visual impairment. This study used a multi-layer relatedness approach to identify novel autophagy-related proteins involved in DR. Three important autophagy-related proteins, TP53, HSAP90AA1, and PIK3R1, were found to be strongly related to detrimental characteristics of DR and may be potential targets for preventing DR progression.
Article
Biochemical Research Methods
Nikhila T. Suresh, Vimina E. Ravindran, Ullattil Krishnakumar
Summary: This study proposes a network-based computational approach to identify key genes and biological pathways shared among diseases through analyzing comorbidity. By organizing genes based on protein-protein interaction networks and using a prioritization algorithm, the study reveals potential relationships between complex disorders such as Diabetes, Obesity, and blood pressure.
CURRENT BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Xiangmao Meng, Ju Xiang, Ruiqing Zheng, Fang-Xiang Wu, Min Li
Summary: Protein complexes play a crucial role in the biological functions of cells. This study proposes a method called DPCMNE to detect protein complexes using multi-level network embedding, which preserves both the local and global topological information of biological networks. Experimental results show that DPCMNE outperforms other existing methods in terms of F1 and F1+Acc, and the protein complexes detected by DPCMNE are biologically more significant.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Naveen Sundar Gnanadesigan, Narmadha Dhanasegar, Manjula Devi Ramasamy, Suresh Muthusamy, Om Prava Mishra, Ganesh Kumar Pugalendhi, Suma Christal Mary Sundararajan, Ashokkumar Ravindaran
Summary: Alzheimer's disease is a neurological illness that causes short-term memory loss, and currently there are no effective therapies for it. Although potential susceptibility genes have been identified, there is still a major challenge in identifying unknown AD-associated genes and drug targets in order to understand the disease mechanisms and develop effective treatments.
Article
Mathematical & Computational Biology
Haseeb Younis, Muhammad Waqas Anwar, Muhammad Usman Ghani Khan, Aisha Sikandar, Usama Ijaz Bajwa
Summary: The study investigated the prediction of protein complexes in protein-protein interaction networks, proposing a new feature selection algorithm and outperforming other algorithms through experiments on multiple datasets.
INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES
(2021)
Article
Multidisciplinary Sciences
Simon Gosset, Annie Glatigny, Melina Gallopin, Zhou Yi, Marion Sale, Marie-Helene Mucchielli-Giorgi
Summary: Protein-protein interactions are crucial for cell processes and analyzing PPI networks can provide insights into protein functions. APPINetwork is a user-friendly open-source package for building and analyzing PPI networks from any species.
Article
Ecology
Chun-Wei Chang, Takeshi Miki, Masayuki Ushio, Po-Ju Ke, Hsiao-Pei Lu, Fuh-Kwo Shiah, Chih-hao Hsieh
Summary: A novel approach for reconstructing high-dimensional interaction Jacobian networks without specific model assumptions was proposed in this study, which successfully identified important species and revealed mechanisms governing the dynamical stability of a bacterial community. The method overcame the challenge of high dimensionality in large natural dynamical systems.
Article
Biochemical Research Methods
Hongjun Chen, Yekai Zhou, Yongjing Liu, Peijing Zhang, Ming Chen
Summary: This study integrated clinical and biomedical research data to systematically mine and analyze pathological proteins and their interaction network in neurodegenerative diseases. It proposed a solution that includes protein isoforms to reveal the impact of protein binding interactions on disease. Finally, a Neurodegenerative Disease Atlas was constructed with interactive 3D molecular graphics.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemistry & Molecular Biology
Panyu Ren, Xiaodi Yang, Tianpeng Wang, Yunpeng Hou, Ziding Zhang
Summary: This study predicted the protein-protein interaction (PPI) network of Cryptosporidium parvum (C. parvum) using three bioinformatics methods and explored the biological significance of the network. The constructed PPI network can serve as a valuable data resource for functional genomics studies and target discovery in drug/vaccine development for C. parvum.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Review
Automation & Control Systems
Yuxin Wu, Deyuan Meng, Zheng-Guang Wu
Summary: This paper reviews different disagreement behaviors in signed networks and discusses the convergence and fluctuation behaviors under static and dynamic topologies. For static signed networks, the behaviors with fixed topologies and switching topologies are investigated, and brief introductions on general time-varying signed networks are provided. For dynamic signed networks, the specific descriptions and characteristics are shown, and the disagreement behaviors can be obtained using the derived static signed graphs. Applications to the behavior analysis of static signed networks with high-order dynamics or communication delays are also presented.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Mathematics, Interdisciplinary Applications
Feri Wijayanto, Karlien Mul, Perry Groot, Baziel G. M. van Engelen, Tom Heskes
Summary: In this paper, a semi-automated method for Rasch analysis based on first principles is proposed, which reduces the need for human input by introducing a novel criterion called IPOQ-LL. The optimization of IPOQ-LL is confirmed to lead to the desired behavior in multi-dimensional and inhomogeneous surveys. Additionally, this method is shown to produce instruments that are practically indistinguishable from those obtained by experts through manual procedures on real-world data sets.
BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY
(2021)
Article
Health Care Sciences & Services
Adriaan Penson, Sylvia van Deuren, Ewald Bronkhorst, Ellen Keizer, Tom Heskes, Marieke J. H. Coenen, Judith G. M. Rosmalen, Wim J. E. Tissing, Helena J. H. van Der Pal, Andrica C. H. de Vries, Marry M. van den Heuvel-Eibrink, Sebastian Neggers, Birgitta A. B. Versluys, Marloes Louwerens, Margriet van der Heiden-van Der Loo, Saskia M. F. Pluijm, Martha Grootenhuis, Nicole Blijlevens, Leontien C. M. Kremer, Eline van Dulmen-den Broeder, Hans Knoop, Jacqueline Loonen
Summary: The DCCSS LATER fatigue study aims to investigate the prevalence of and factors associated with CRF in childhood cancer survivors, proposing a model that identifies predisposing, triggering, maintaining, and moderating factors.
BMC MEDICAL RESEARCH METHODOLOGY
(2021)
Article
Physics, Multidisciplinary
Errol Zalmijn, Tom Heskes, Tom Claassen
Summary: Semiconductor lithography systems, like natural complex systems, exhibit nonlinear dynamics and face challenges in efficiently diagnosing issues due to high-dimensionality and non-stationarity of data.
Article
Biochemical Research Methods
Yuliya Shapovalova, Tom Heskes, Tjeerd Dijkstra
Summary: Understanding the synergistic and antagonistic effects of drug and toxin combinations is crucial for various applications. Different models, such as Loewe additivity, Bliss independence, Hand model, and MuSyC model, are used to evaluate synergy by comparing the response of drug combinations to predicted non-interactive responses. The newly proposed Hand-GP model, which combines the Hand model with Gaussian processes, is shown to outperform other standard synergy models in capturing synergy in response patterns.
BMC BIOINFORMATICS
(2022)
Review
Biochemistry & Molecular Biology
Christiaan de Leeuw, Jeanne Savage, Ioan Gabriel Bucur, Tom Heskes, Danielle Posthuma
Summary: With the availability of large genetic data sets, Mendelian Randomization (MR) has become popular as a secondary analysis method. Using genetic variants as instrumental variables, MR can estimate causal effects between phenotypes when experimental research is not feasible. However, strong assumptions are required, and not meeting these assumptions can lead to biased results. Therefore, understanding and evaluating these assumptions is crucial when using MR.
EUROPEAN JOURNAL OF HUMAN GENETICS
(2022)
Article
Clinical Neurology
Ka-Hoo Lam, Ioan Gabriel Bucur, Pim Van Oirschot, Frank De Graaf, Hans Weda, Eva Strijbis, Bernard Uitdehaag, Tom Heskes, Joep Killestein, Vincent De Groot
Summary: The use of a smartphone-adapted Symbol Digit Modalities Test (sSDMT) allows for individualized monitoring of cognitive impairment in multiple sclerosis (MS) patients. By utilizing a local linear trend model, the detection of reliable changes in sSDMT scores is improved. This fine-grained monitoring approach can complement current clinical assessment and enhance clinical care in MS.
MULTIPLE SCLEROSIS AND RELATED DISORDERS
(2022)
Article
Ecology
Konrad P. Mielke, Aafke M. Schipper, Tom Heskes, Michiel C. Zijp, Leo Posthuma, Mark A. J. Huijbregts, Tom Claassen
Summary: Understanding ecological responses to environmental changes is crucial for conserving biodiversity. Experimental studies are standard to identify cause-effect relationships, but deriving these relationships from observational data is challenging due to potential confounding influences. A new causal discovery algorithm can reveal ecological networks in rivers and streams, providing insights into the causes of reductions in fish and invertebrate community integrity.
FRONTIERS IN ECOLOGY AND EVOLUTION
(2022)
Article
Rehabilitation
Karlien Mul, Feri Wijayanto, Tom G. J. Loonen, Perry Groot, Sanne C. C. Vincenten, Simone Knuijt, Jan T. Groothuis, Thomas J. J. Maal, Tom Heskes, Nicol C. Voermans, Baziel G. M. van Engelen
Summary: This study developed a functional assessment measure for evaluating the functional disabilities associated with facial weakness in facioscapulohumeral muscular dystrophy (FSHD). The measure demonstrated good reliability and validity, and can be used as a tool for further research.
DISABILITY AND REHABILITATION
(2023)
Article
Acoustics
Martijn Schilpzand, Chase Neff, Jeroen van Dillen, Bram van Ginneken, Tom Heskes, Chris de Korte, Thomas van den Heuvel
Summary: This study presents a method to automatically detect low-lying placenta or placenta previa from 2-D ultrasound imaging using a deep learning model. The method achieved high accuracy in placenta segmentation and classification, and showed feasibility in resource-limited settings.
ULTRASOUND IN MEDICINE AND BIOLOGY
(2022)
Meeting Abstract
Clinical Neurology
Matthieu de Hemptinne, Tom Heskes, Danielle Posthuma
EUROPEAN NEUROPSYCHOPHARMACOLOGY
(2022)
Article
Social Sciences, Mathematical Methods
Feri Wijayanto, Ioan Gabriel Bucur, Perry Groot, Tom Heskes
Summary: autoRasch is an R package that allows for (semi-)automated Rasch analysis by optimizing the IPOQ-LL or IPOQ-LL-DIF. It fits the GPCM or GPCM-DIF using PJMLE and provides standard statistics for Rasch analyses. The package also allows for manual Rasch analysis based on the automated method's output.
APPLIED PSYCHOLOGICAL MEASUREMENT
(2022)
Article
Clinical Neurology
Amir H. Talebi, Jan H. L. Ypinga, Nienke M. De Vries, Jorik Nonnekes, Marten Munneke, Bas R. Bloem, Tom Heskes, Yoav Ben-Shlomo, Sirwan K. L. Darweesh
Summary: Specialized physiotherapy and occupational therapy can reduce the incidence rate of Parkinson's disease-related complications. There may be a synergistic effect among multiple specialized allied health disciplines. The findings of this study support the introduction of specialized allied health therapy expertise in Parkinson's disease care.
MOVEMENT DISORDERS
(2023)
Article
Clinical Neurology
Ka-Hoo Lam, Ioan Gabriel Bucur, Pim Van Oirschot, Frank De Graaf, Eva Strijbis, Bernard Uitdehaag, Tom Heskes, Joep Killestein, Vincent De Groot
Summary: This study investigated the use of remote smartphone-based 2-minute walking tests (s2MWTs) in assessing and detecting changes in ambulatory function in multiple sclerosis (MS) patients. The results showed that s2MWTs had large variability and were not sensitive to changes in clinical outcomes. However, individual-level curve fitting analysis was able to reduce variability and detect statistically reliable changes in ambulatory function in 45% of patients.
MULTIPLE SCLEROSIS JOURNAL
(2023)
Article
Clinical Neurology
Max J. J. Oosterwegel, Jesse H. H. Krijthe, Melina G. H. E. den Brok, Lieneke van den Heuvel, Edo Richard, Tom Heskes, Bastiaan R. R. Bloem, Luc J. W. Evers
Summary: This study found no clinically significant effects of cardiovascular risk factors on the clinical progression of Parkinson's disease, based on the analysis of two large cohorts of de novo PD patients.
FRONTIERS IN NEUROLOGY
(2023)
Meeting Abstract
Clinical Neurology
P. C. G. Molenaar, P. van Oirschot, I. Bucur, K. Lam, B. Moraal, T. Heskes, V. de Groot, B. Uitdehaag, J. Killestein, E. Strijbis
MULTIPLE SCLEROSIS JOURNAL
(2022)