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Cavity approach for the approximation of spectral density of graphs with heterogeneous structures

Physical Review E 2024年第3期109卷 034303-034303页

作者： Grover E. C. Guzman Peter F. Stadler Andre Fujita Department of Computer Science Institute of Mathematics and Statistics University of São Paulo Rua do Matão 1010 São Paulo - SP 05508-090 Brazil Bioinformatics Group Department of Computer Science Interdisciplinary Center for Bioinformatics School of Excellence in Embedded Composite AI Dresden/Leipzig (SECAI) Leipzig University Härtelstraße 16-18 D-04107 Leipzig Germany German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Puschstraße 4 04103 Leipzig Germany Competence Center for Scalable Data Services and Solutions Dresden-Leipzig Humboldtstraße 25 04105 Leipzig Germany Leipzig University Härtelstraße 16-18 D-04107 Leipzig Germany Max Planck Institute for Mathematics in the Sciences Inselstraße 22 D-04103 Leipzig Germany Institute for Theoretical Chemistry University of Vienna Währingerstraße 17 A-1090 Wien Austria Facultad de Ciencias Universidad Nacional de Colombia Sede Bogotá 111321 Colombia and The Santa Fe Institute 1399 Hyde Park Road Santa Fe New Mexico 87501 USA Department of Computer Science Institute of Mathematics and Statistics University of São Paulo Rua do Matão 1010 São Paulo - SP 05508-090 Brazil and Division of Network AI Statistics Medical Institute of Bioregulation Kyushu University Fukuoka 812-8582 Japan

Graphs have become widely used to represent and study social, biological, and technological systems. Statistical methods to analyze empirical graphs were proposed based on the graph's spectral density. However, their running time is cubic in the number of vertices, precluding direct application to large instances. Thus, efficient algorithms to calculate the spectral density become necessary. For sparse graphs, the cavity method can efficiently approximate the spectral density of locally treelike undirected and directed graphs. However, it does not apply to most empirical graphs because they have heterogeneous structures. Thus, we propose methods for undirected and directed graphs with heterogeneous structures using a new vertex's neighborhood definition and the cavity approach. Our methods' time and space complexities are O(|E|hmax3t) and O(|E|hmax2t), respectively, where |E| is the number of edges, hmax is the size of the largest local neighborhood of a vertex, and t is the number of iterations required for convergence. We demonstrate the practical efficacy by estimating the spectral density of simulated and real-world undirected and directed graphs.

关键词： Network structure Directed networks Monte Carlo methods Network Models Topological tools

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Killer cell immunoglobulin receptor diversity and its relevance in the human host’s response to HIV infection in African populations

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Translational Medicine Communications 2023年第1期8卷 1-9页

作者： John Mukisa Marion Amujal Obondo J. Sande Moses L. Joloba David P. Kateete Daudi Jjingo Graeme Mardon Neil Hanchard Mogomotsi Matshaba Jill A. Hollenbach Department of Immunology and Molecular Biology College of Health Sciences Makerere University P.O.BOX 7072 Kampala Uganda College of Computing and Information Sciences Makerere University Kampala Uganda African Center of Excellence in Bioinformatics and Data Science Infectious Diseases Institute (IDI) Makerere University Kampala Uganda Department of Molecular and Human Genetics and Department of Pathology and Immunology Baylor College of Medicine Houston TX USA National Human Genome Research Institute Bethesda MD USA Botswana-Baylor Children’s Clinical Centre of Excellence P/Bag BR 129 Gaborone Botswana Department of Neurology and Department of Epidemiology and Biostatistics University of California San Francisco San Francisco California 94158 USA

Host response to the human immune deficiency virus (HIV) involves both the innate and adaptive immune systems. As part of the innate immune system, the killer cell immunoglobulin-like receptors (KIRs) found on natural killer cells and some T-lymphocytes are genetically diverse and play key functions in the host response against viral pathogens. In the last decade, there has been substantial growth in sequencing technologies and bioinformatics capacity to understand human host genetics, including KIR. However, there is limited literature on how the KIR diversity informs the perspectives on HIV disease states in understudied African settings. A better understanding of the effects of KIRs on the host’s immune response to HIV in African settings is essential to inform strategies to develop more effective therapies and vaccines to improve health among people living with HIV (PLWH). In this paper, we review KIR diversity, the role of KIR immunogenetic variation in the human host response to HIV, discuss current perspectives on the studies to assess the relationship between KIR diversity and the HIV disease continuum, and suggest future research prospects.

关键词： Killer cell immunoglobulin-like receptors ( ) Diversity Human immune deficiency virus (HIV) bioinformatics

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What makes a reaction network "chemical"?

arXiv

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arXiv 2022年

作者： Müller, Stefan Flamm, Christoph Stadler, Peter F. Faculty of Mathematics University of Vienna Oskar-Morgenstern-Platz 1 WienA-1090 Austria Department of Theoretical Chemistry University of Vienna Währinger Straße 17 WienA-1090 Austria Bioinformatics Group Department of Computer Science Interdisciplinary Center for Bioinformatics Universität Leipzig Härtelstraße 16-18 LeipzigD-04107 Germany Halle-Jena-Leipzig & Competence Center for Scalable Data Services and Solutions Dresden-Leipzig Leipzig Research Center for Civilization Diseases University Leipzig LeipzigD-04107 Germany Max Planck Institute for Mathematics in the Sciences Inselstraße 22 LeipzigD-04103 Germany Faculdad de Ciencias Universidad Nacional de Colombia Sede Bogotá Ciudad Universitaria DC BogotáCOL-111321 Colombia Santa Fe Institute 1399 Hyde Park Road Santa FeNM87501 United States

Background: Reaction networks (RNs) comprise a set X of species and a set R of reactions Y → Y′, each converting a multiset of educts Y ⊆ X into a multiset Y′ ⊆ X of products. RNs are equivalent to directed hypergraphs. However, not all RNs necessarily admit a chemical interpretation. Instead, they might contradict fundamental principles of physics such as the conservation of energy and mass or the reversibility of chemical reactions. The consequences of these necessary conditions for the stoichiometric matrix S ∈ X×R have been discussed extensively in the chemical literature. Here, we provide sufficient conditions for S that guarantee the interpretation of RNs in terms of balanced sum formulas and structural formulas, respectively. Results: Chemically plausible RNs allow neither a perpetuum mobile, i.e., a "futile cycle" of reactions with non-vanishing energy production, nor the creation or annihilation of mass. Such RNs are said to be thermodynamically sound and conservative. For finite RNs, both conditions can be expressed equivalently as properties of the stoichiometric matrix S. The first condition is vacuous for reversible networks, but it excludes irreversible futile cycles and – in a stricter sense – futile cycles that even contain an irreversible reaction. The second condition is equivalent to the existence of a strictly positive reaction invariant. Furthermore, it is sufficient for the existence of a realization in terms of sum formulas, obeying conservation of "atoms". In particular, these realizations can be chosen such that any two species have distinct sum formulas, unless S implies that they are "obligatory isomers". In terms of structural formulas, every compound is a labeled multigraph, in essence a Lewis formula, and reactions comprise only a rearrangement of bonds such that the total bond order is preserved. In particular, for every conservative RN, there exists a Lewis realization, in which any two compounds are realized by pairwisely distinct mu

关键词： Energy conservation

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia Computer Science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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U1 snRNP regulates alternative promoter activity by inhibiting premature polyadenylation

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Molecular Cell 2025年第10期85卷 1968-1981.e7页

作者： Kim, GyeungYun Carroll, Christine L. Wakefield, Zachary Peters Tuncay, Mustafa Fiszbein, Ana Biology Department Boston University Boston 02215 United States Graduate Program in Molecular Biology Cell Biology & Biochemistry Boston University Boston 02215 United States Graduate Program in Cell and Molecular Biology Boston University Boston 02215 United States Bioinformatics Program Faculty of Computing and Data Science Boston University Boston 02215 United States Center for Computing & Data Sciences Boston University Boston 02215 United States

Emerging evidence indicates that splicing factors mediate the close link between transcription and splicing. However, the mechanisms underlying this coupling remain unclear. U1 small nuclear ribonucleoprotein particle (U1 snRNP) not only initiates splicing but also plays a crucial role in preventing premature cleavage and polyadenylation, facilitating long-distance transcriptional elongation. Here, we show that U1 snRNP regulates alternative promoter activity in human cells by inhibiting premature polyadenylation. In genes carrying premature polyadenylation sites between two promoters, U1 snRNP inhibition with antisense oligonucleotides leads to a significant decrease in downstream promoter activity. Conversely, restoring U1 snRNP activity or inhibiting premature polyadenylation rescues downstream promoter activity. Mechanistically, U1 snRNP inhibition correlates with reduced chromatin accessibility, decreased RNA polymerase II serine 5 phosphorylation, and increased promoter-proximal pause at downstream promoters. Our findings support a model in which U1 snRNP favors productive elongation from upstream promoters, triggering downstream promoter activation by destabilizing nucleosomes and promoting promoter escape. © 2025 The Author(s)

关键词： alternative promoters dowsntream promoters promoter-proximal pause splicing factors splicing transcription transcription cooperativity transcription initiation transcription interfierence transcription start sites U1 snRNP

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Digitizing Farmers' Land data Collection Systems in Indonesia with the Use of Tani Millenial Apps

Digitizing Farmers' Land Data Collection Systems in Indonesi...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mohammad Prasanto Bimantio Dian Pratama Putra Teddy Suparyanto Amallia Ferhat Nanda Satya Nugraha Alam Ahmad Hidayat Bens Pardamean Department of Food and Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia Department of Agrotechnology Institute of Agriculture STIPER Yogyakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Agricultural Socio-Economics Institute of Agriculture STIPER Yogyakarta Indonesia Department of Forestry Institute of Agriculture STIPER Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453967

In this era of digital world information, farmers face challenges about information management of huge data and the complexity of processes in precision farming. The data collection carried out so far can cause several difficulties, especially if the data is needed by the government or academics to support decision-making. Agricultural data collection applications only cover 12% of the market share of Android-based agriculture-based applications. In this study, Tani Milenial application is present as an alternative to support agricultural data collection activities in Indonesia. This application encourages farmers to be active and contribute independently to their role as subjects of agricultural development and is accustomed to digitally recording their agricultural activities. In this developed application system, the community, especially farmers and farmer groups, will find it easier to get information about agricultural potential data around where they carry out agricultural activities and can access this information online. Tani Milenial works as a guide to help farmers and transform agriculture but still have some gaps which should be checked and removed. The data collected can be used by various parties for research and decision-making. The app can be further improved to develop new features related to education, market information, and goods.

关键词： Decision making Education Government Transforms data collection Agriculture Recording

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Lung Cancer 2025年 204卷 108584-108584页

作者： Nomura, Shogo Sekino, Yuta Shiraishi, Yoshimasa Toi, Yukihiro Yoshida, Tatsuya Tanaka, Kentaro Suzuki, Shinichiro Azuma, Koichi Hara, Satoshi Morita, Ryo Niho, Seiji Koda, Takuyuki Toyozawa, Ryo Yoh, Kiyotaka Kurata, Takayasu Fukuda, Haruhiko Ohe, Yuichiro Okamoto, Isamu Japan Clinical Oncology Group Data Center/Operations Office National Cancer Center Hospital Tokyo Japan Department of Biostatistics and Bioinformatics of Medicine The University of Tokyo Tokyo Japan Department of Respiratory Medicine of Medical Sciences Kyushu University Fukuoka Japan Department of Pulmonary Medicine Sendai Kousei Hospital Miyagi Sendai Japan Department of Thoracic Oncology National Cancer Center Hospital Tokyo Japan Department of Medical Oncology Kindai University Faculty of Medicine Osaka-Sayama Osaka Japan Division of Respirology Neurology and Rheumatology Department of Internal Medicine Kurume University School of Medicine Fukuoka Japan Department of Respiratory Medicine Itami City Hospital Hyogo Japan Department of Respiratory Medicine Akita Kousei Medical Center Akita Japan Department of Pulmonary Medicine and Clinical Immunology Dokkyo Medical University School of Medicine Tochigi Japan Department of Respiratory Medicine Ohara Healthcare Foundation Kurashiki Central Hospital Okayama Japan Department of Thoracic Oncology NHO Kyushu Cancer Center Fukuoka Japan Department of Thoracic Oncology National Cancer Center Hospital East Chiba Japan Department of Thoracic Oncology Kansai Medical University Osaka Japan

Background: Combined chemotherapy with nivolumab and ipilimumab (NIC) improves survival outcomes in treatment-naïve patients with advanced non-small cell lung cancer (NSCLC). However, these patients have a higher incidence of treatment-related deaths (TRDs), especially due to NIC. This study aimed to devise a risk stratification score for selecting patients with lower or higher TRD risk. Methods: A dataset from the JCOG2007 study was used, which compared NIC with combined chemotherapy with pembrolizumab (PC). The TRD score was built from an adaptive LASSO regression analysis. Results: The JCOG2007 study randomly assigned 295 patients to the PC (n = 147) and NIC (n = 148) arms, respectively. The TRD score was constructed for 124 patients who underwent NIC and had no missing covariates. The dichotomized TRD score was built and stratified all treated 290 (all enrolled 295) patients into 92 (92) high-risk and 198 (203) low-risk patients. No apparent differences in TRD incidence were observed in low-risk patients (2.2 % [0/92] with PC and 2.8 % [3/106] with NIC);however, this difference was noteworthy in high-risk patients (1.9 % [1/52] with PC and 20.0 % [8/40] with NIC). Of the 295 patients, the hazard ratios for death were 0.894 (0.553–1.444) in low-risk patients and that was 1.215 [0.696‐2.122] in high-risk patients. Worse outcomes in the NIC arm were consistently observed for both immune-related adverse events (irAEs) and progression-free survival. Conclusions: Although further validation studies with external data inside and outside Japan are required, the TRD score is a valuable tool for identifying patients with comparable toxicity-efficacy profiles among PC and NIC regimens. © 2025 Elsevier B.V.

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Developing a practical neurodevelopmental prediction model for targeting high-risk very preterm infants during visit after NICU: a retrospective national longitudinal cohort study

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BMC Medicine 2024年第1期22卷 68-68页

作者： Chung, Hao Wei Chen, Ju-Chieh Chen, Hsiu-Lin Ko, Fang-Yu Ho, Shinn-Ying Chang, Jui-Hsing Tsou, Kuo-Inn Tsao, Po-Nien Mu, Shu-Chi Hsu, Chyong-Hsin Lien, Reyin Lin, Hung-Chih Hsiao, Chien-Chou Huang, Chao-Ching Chen, Chih-Cheng Division of Neonatology Department of Pediatrics Kaohsiung Medical University Chung-Ho Memorial Hospital Kaohsiung Medical University Kaohsiung Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Pediatrics Kaohsiung Municipal Siaogang Hospital Kaohsiung Medical University Kaohsiung Taiwan Center for Big Data Research Kaohsiung Medical University Kaohsiung Taiwan Department of Respiratory Therapy College of Medicine Kaohsiung Medical University Kaohsiung Taiwan Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Center for Intelligent Drug Systems and Smart Bio-Devices National Yang Ming Chiao Tung University Hsinchu Taiwan College of Health Sciences Kaohsiung Medical University Kaohsiung Taiwan

BACKGROUND: Follow-up visits for very preterm infants (VPI) after hospital discharge is crucial for their neurodevelopmental trajectories, but ensuring their attendance before 12 months corrected age (CA) remains a challenge. Current prediction models focus on future outcomes at discharge, but post-discharge data may enhance predictions of neurodevelopmental trajectories due to brain plasticity. Few studies in this field have utilized machine learning models to achieve this potential benefit with transparency, explainability, and transportability. METHODS: We developed four prediction models for cognitive or motor function at 24 months CA separately at each follow-up visits, two for the 6-month and two for the 12-month CA visits, using hospitalized and follow-up data of VPI from the Taiwan Premature Infant Follow-up Network from 2010 to 2017. Regression models were employed at 6 months CA, defined as a decline in The Bayley Scales of Infant Development 3rd edition (BSIDIII) composite score > 1 SD between 6- and 24-month CA. The delay models were developed at 12 months CA, defined as a BSIDIII composite score < 85 at 24 months CA. We used an evolutionary-derived machine learning method (EL-NDI) to develop models and compared them to those built by lasso regression, random forest, and support vector machine. RESULTS: One thousand two hundred forty-four VPI were in the developmental set and the two validation cohorts had 763 and 1347 VPI, respectively. EL-NDI used only 4-10 variables, while the others required 29 or more variables to achieve similar performance. For models at 6 months CA, the area under the receiver operating curve (AUC) of EL-NDI were 0.76-0.81(95% CI, 0.73-0.83) for cognitive regress with 4 variables and 0.79-0.83 (95% CI, 0.76-0.86) for motor regress with 4 variables. For models at 12 months CA, the AUC of EL-NDI were 0.75-0.78 (95% CI, 0.72-0.82) for cognitive delay with 10 variables and 0.73-0.82 (95% CI, 0.72-0.85) for motor delay with 4 variable

关键词： Machine learning Neurodevelopmental outcome Prediction model Very preterm

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BIPSPI+: Mining Type-Specific datasets of Protein Complexes to Improve Protein Binding Site Prediction

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Journal of Molecular Biology 2022年第11期434卷 167556-167556页

作者： Sanchez-Garcia, R. Macias, J.R. Sorzano, C.O.S. Carazo, J.M. Segura, J. Biocomputing Unit National Center for Biotechnology (CSIC) Darwin 3 Campus Univ. Autónoma de Madrid Cantoblanco Madrid 28049 Spain Oxford Protein Informatics Group Department of Statistics University of Oxford 29 St Giles' Oxford OX1 3LB UK United Kingdom Research Collaboratory for Structural Bioinformatics Protein Data Bank San Diego Supercomputer Center University of California San Diego La Jolla 92093 CA United States

Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating the specific residues that compose the interface of protein complexes. In recent years, new machine learning and other algorithmic approaches have been proposed to solve this problem. However, little effort has been made in finding better training datasets to improve the performance of these methods. With the aim of vindicating the importance of the training set compilation procedure, in this work we present BIPSPI+, a new version of our original server trained on carefully curated datasets that outperforms our original predictor. We show how prediction performance can be improved by selecting specific datasets that better describe particular types of protein interactions and interfaces (e.g. homo/hetero). In addition, our upgraded web server offers a new set of functionalities such as the sequence-structure prediction mode, hetero- or homo-complex specialization and the guided docking tool that allows to compute 3D quaternary structure poses using the predicted interfaces. BIPSPI+ is freely available at https://***. © 2022 The Authors

关键词： binding site machine learning protein interactions web server

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IoT Solution for Intelligent Pond Monitoring 3

IoT Solution for Intelligent Pond Monitoring

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3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Darmalim, Usin Darmalim, Ferdinan Darmalim, Sutristo Hidayat, Alam Ahmad Budiarto, Arif Mahesworo, Bharuno Pardamean, Bens Mega Medica Pharmaceuticals Jakarta11840 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Channa striata or the striped snakehead fish is one of snakehead fish species which inhabits all types of freshwater bodies distributed across Asian countries. Because this fish is known to have higher albumin fraction (64.61%) of protein and other economic values, domestication, and cultivation of this fish has been done in many Asian countries such as Indonesia, China, Malaysia, Thailand, Bangladesh, and India. Environmental factors such as temperature, water pH, dissolved oxygen, total dissolved solids, and turbidity are important parameters must be considered inbreeding and growing this type of fish. The aim of this paper is to propose an IoT solution to automatically monitor these environmental factors. It is designed with affordable and open-source electrical components to provide a cost-efficient solution for farmers. Five sensors are used to measure each parameter. A web application prototype is also presented as a companion application for the users to get useful information from the IoT device. It is developed using a Pythonframework. By accessing this web application, the users can immediately detect any abnormal conditions of the pond. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Fish

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