Journal of Integrative Bioinformatics最新文献

Obtaining PDC and other high-added value products from lignin by in silico genetic engineering in Novosphingobium aromaticivorans. 利用硅基因工程技术从木质素中获得PDC等高附加值产品。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2026-02-25 eCollection Date: 2025-09-01 DOI: 10.1515/jib-2024-0059

Isabel María Fernández, Francisco Guil, José Manuel García

{"title":"Obtaining PDC and other high-added value products from lignin by in silico genetic engineering in Novosphingobium aromaticivorans.","authors":"Isabel María Fernández, Francisco Guil, José Manuel García","doi":"10.1515/jib-2024-0059","DOIUrl":"10.1515/jib-2024-0059","url":null,"abstract":"Lignin, the second most abundant plant biopolymer on Earth, is produced in large quantities as waste material by many industries. Researchers have studied bacterial metabolic networks as potential candidates for integrating lignin into a biotechnological value chain. The GEM used in this work for metabolic engineering is iNovo479, which simulates the metabolism of Novosphingobium aromaticivorans DSM12444. We have conducted a study on PDC production and found several intervention strategies to help achieve this goal. These strategies include more than just blocking the ligI gene, which has been a well-known approach. Although these new strategies resulted in a lower yield of PDC relative to biomass formed, they led to a higher cell yield than deleting the ligI gene. The research presented in this paper focuses on the production of high-value compounds from lignin. Previous studies have used mutated microorganisms to produce these bioproducts from large amounts of glucose. However, biosynthesis from lignin would improve productivity and make the fermentation process more cost-effective. Through gene knockouts, we have discovered ways to ensure a minimum production of bioproducts such as acetaldehyde, citrate, glutarate, glycerol, phenol, and propanoate when growing the N. aromaticivorans strain using lignin-derived compounds as unique substrates.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13066346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147322172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Systems biology graphical notation: process description language level 1 version 2.1. 系统生物学图形符号：过程描述语言1级2.1版。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2026-01-23 DOI: 10.1515/jib-2025-0018

Hasan Balci, Adrien Rougny, Rupert Overall, Irina Balaur, Michael L Blinov, Hanna Borlinghaus, Emek Demir, Andreas Dräger, Robin Haw, Alexander Mazein, Huaiyu Mi, Stuart Moodie, Falk Schreiber, Anatoly Sorokin, Vasundra Touré, Alice Villéger, Tobias Czauderna, Ugur Dogrusoz, Augustin Luna

{"title":"Systems biology graphical notation: process description language level 1 version 2.1.","authors":"Hasan Balci, Adrien Rougny, Rupert Overall, Irina Balaur, Michael L Blinov, Hanna Borlinghaus, Emek Demir, Andreas Dräger, Robin Haw, Alexander Mazein, Huaiyu Mi, Stuart Moodie, Falk Schreiber, Anatoly Sorokin, Vasundra Touré, Alice Villéger, Tobias Czauderna, Ugur Dogrusoz, Augustin Luna","doi":"10.1515/jib-2025-0018","DOIUrl":"10.1515/jib-2025-0018","url":null,"abstract":"The Systems Biology Graphical Notation (SBGN) is an international community effort to standardize the visualization of pathways and networks, making them accessible to scientists from diverse fields while facilitating efficient and ac-curate knowledge exchange among research communities, industry, and other stakeholders in systems biology. SBGN consists of three complementary languages - Entity Relationship (ER), Activity Flow (AF), and Process Description (PD) - each addressing biological and biochemical systems at varying levels of detail. PD, closely aligned with the metabolic and regulatory pathways found in biological literature, books, and academic courses, provides well-defined semantics for precisely representing biological information. The PD language uses a graph structure to represent mechanistic and temporal relationships of biological interactions and transformations. It incorporates distinct node types, including entity pools (e.g., metabolites, proteins, genes, and complexes) and processes (e.g., reactions and associations), with edges representing the connections between nodes (e.g., consumption, production, stimulation, and inhibition). This document details Level 1 Version 2.1 of the PD specification, including several improvements over the previous version (Level 1 Version 2.0): 1) refinements to document structure and terminology, 2) clarifications and updates to specification content, and 3) updated figures and rules.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146031556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Functional and evolutionary characteristics of human genes encoding cell surface receptors involved in the regulation of appetite. 参与食欲调节的细胞表面受体编码基因的功能和进化特征。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2026-01-08 eCollection Date: 2025-09-01 DOI: 10.1515/jib-2025-0023

Elena Ignatieva, Sergey Lashin, Roman Ivanov, Valentin Suslov, Angelina Mikhailova, Nikolay Kolchanov

{"title":"Functional and evolutionary characteristics of human genes encoding cell surface receptors involved in the regulation of appetite.","authors":"Elena Ignatieva, Sergey Lashin, Roman Ivanov, Valentin Suslov, Angelina Mikhailova, Nikolay Kolchanov","doi":"10.1515/jib-2025-0023","DOIUrl":"10.1515/jib-2025-0023","url":null,"abstract":"Appetite is an instinct that has been formed through evolution. Appetite promotes normal growth and development in humans. However, under conditions of food abundance, appetite can become excessive, posing significant health risks. In this study we have identified 80 human genes whose orthologs regulated food intake in model animal species. More than 80 % of these genes encode G-protein-coupled receptors and 29 % were found to be involved in developmental processes. Using phylostratigraphic age index (PAI), which specifies the evolutionary age of a gene, we found that this set of 80 genes contains an increased proportion of genes with the same phylostratigraphic age (PAI = 6, the stage of Vertebrata divergence) indicating the coordinated evolution of this group of genes. Using divergence index (DI), which indicates the type of selection to which the gene is subjected, we observed significant enrichment for genes with DI ≤ 0.25, i.e., those that are subject to strong stabilizing selection. The subgroup of genes having DI ≤ 0.25 included 45 genes and was enriched with genes that are associated with developmental processes. This finding supports the hypothesis that developmental disturbances generally impose strong constraints on viability due to purifying selection.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13066349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145913868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Streamlining feature elaboration and statistics analysis in metabolomics: the GetFeatistics R-package. 简化代谢组学中的特征阐述和统计分析：getfeatatistics r包。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-12-24 DOI: 10.1515/jib-2025-0047

Gianfranco Frigerio

{"title":"Streamlining feature elaboration and statistics analysis in metabolomics: the GetFeatistics R-package.","authors":"Gianfranco Frigerio","doi":"10.1515/jib-2025-0047","DOIUrl":"https://doi.org/10.1515/jib-2025-0047","url":null,"abstract":"Metabolomics studies require complex data processing pipelines to ensure data quality and extract meaningful biological insights. GetFeatistics is an R-package developed to streamline the elaboration and statistical analysis of metabolomics data. For targeted analyses, the package enables calibration curve-based quantification with different data weighting options. For untargeted studies, it includes dedicated functions to import feature tables from tools like patRoon and MS-DIAL, assign annotation confidence levels, and filter features based on pooled quality control (QC) criteria, including options for group-specific pooled QCs. The package also provides functions for univariate and multivariate statistical analyses, notably streamlined regression modelling with fixed effects, mixed-effects models for longitudinal data, and Tobit regression for censoring values exceeding the limits of detection. Output tables are concise and informative, facilitating interpretation and reporting, while output visualisations are fully customisable via the ggplot grammar. Additional functionalities include automated retrieval of chemical properties from PubChem, ontology classification via ClassyFire, and pathway enrichment analysis using the FELLA package. GetFeatistics is publicly available on GitHub, with comprehensive documentation and a step-by-step vignette. By integrating key steps of the metabolomics workflow, the package aims to facilitate both exploratory studies and large-scale epidemiological applications in metabolomics research.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145812266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Colon cancer survival prediction from gland shapes within histology slides using deep learning. 利用深度学习从组织学切片中的腺体形状预测结肠癌存活。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-07-14 eCollection Date: 2025-06-01 DOI: 10.1515/jib-2024-0052

Rawan Gedeon, Atulya Nagar

{"title":"Colon cancer survival prediction from gland shapes within histology slides using deep learning.","authors":"Rawan Gedeon, Atulya Nagar","doi":"10.1515/jib-2024-0052","DOIUrl":"10.1515/jib-2024-0052","url":null,"abstract":"This study investigates the application of deep learning techniques for segmenting glands in histopathological images of colorectal cancer. We trained two convolutional neural network models, U-Net and DCAN, on a combination of the GlaS and CRAG datasets to enhance generalization across diverse histological appearances, selecting DCAN for its superior accuracy in delineating gland boundaries. The goal was to achieve robust gland segmentation applicable to whole slide images (WSIs) from The Cancer Genome Atlas (TCGA). Using the segmented glands, we extracted patient-level morphological features and used them to predict survival outcomes. A Cox proportional hazards model was trained on these features and achieved a high concordance index, indicating strong predictive performance. Patients were then stratified into high- and low-risk groups, with significant differences in survival distributions (log-rank p-value: 0.01317). In addition, we benchmarked our models against state-of-the-art gland segmentation methods on GlaS and CRAG, highlighting the trade-off between domain-specific accuracy and cross-dataset robustness.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12569585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Editorial - 20 years Journal of Integrative Bioinformatics. 编辑- 20 年整合生物信息学杂志。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-07-09 eCollection Date: 2025-03-01 DOI: 10.1515/jib-2025-0034

Ralf Hofestädt

引用次数: 0

Sustainable software development in science - insights from 20 years of Vanted. 科学中的可持续软件开发-来自20 年Vanted的见解。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-07-01 eCollection Date: 2025-03-01 DOI: 10.1515/jib-2025-0007

Falk Schreiber, Tobias Czauderna, Dimitar Garkov, Niklas Gröne, Karsten Klein, Matthias Lange, Uwe Scholz, Björn Sommer

引用次数: 0

Metagenome and metabolome study on inhaled corticosteroids in asthma patients with side effects. 哮喘患者吸入皮质类固醇副作用的宏基因组和代谢组研究。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-06-24 eCollection Date: 2025-09-01 DOI: 10.1515/jib-2024-0062

Igor Goryanin, Anatoly Sorokin, Meder Seitov, Berik Emilov, Muktarbek Iskakov, Irina Goryanin, Batyr Osmonov

引用次数: 0

Leveraging transformers for semi-supervised pathogenicity prediction with soft labels. 利用变压器进行软标签的半监督致病性预测。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-06-23 eCollection Date: 2025-06-01 DOI: 10.1515/jib-2024-0047

Pablo Enrique Guillem, Marco Zurdo-Tabernero, Noelia Egido Iglesias, Ángel Canal-Alonso, Liliana Durón Figueroa, Guillermo Hernández, Angélica González-Arrieta, Fernando de la Prieta

{"title":"Leveraging transformers for semi-supervised pathogenicity prediction with soft labels.","authors":"Pablo Enrique Guillem, Marco Zurdo-Tabernero, Noelia Egido Iglesias, Ángel Canal-Alonso, Liliana Durón Figueroa, Guillermo Hernández, Angélica González-Arrieta, Fernando de la Prieta","doi":"10.1515/jib-2024-0047","DOIUrl":"10.1515/jib-2024-0047","url":null,"abstract":"The rapid advancement of Next-Generation Sequencing (NGS) technologies has revolutionized the field of genomics, producing large volumes of data that necessitate sophisticated analytical techniques. This paper introduces a Deep Learning model designed to predict the pathogenicity of genetic variants, a vital component in advancing personalized medicine. The model is trained on a dataset derived from the analysis of NGS outputs, containing a combination of well-defined and ambiguous genetic variants. By employing a semi-supervised learning approach, the model efficiently utilizes both confidently labeled and less certain data. At the core of the methodology is the Feature Tokenizer Transformer architecture, which processes both numerical and categorical genomic information. The preprocessing pipeline includes key steps such as data imputation, scaling, and encoding to ensure high data quality. The results highlight the model's impressive accuracy, particularly in detecting confidently labeled variants, while also addressing the impact of its predictions on less certain (soft-labeled) data.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12569578/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144334418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Petri net modeling and simulation of post-transcriptional regulatory networks of human embryonic stem cell (hESC) differentiation to cardiomyocytes. 人胚胎干细胞（hESC）向心肌细胞分化的转录后调控网络的Petri网建模和模拟。

IF 1.8

Journal of Integrative Bioinformatics Pub Date : 2025-06-23 eCollection Date: 2025-03-01 DOI: 10.1515/jib-2024-0037

Aruana F F Hansel-Fröse, Christoph Brinkrolf, Marcel Friedrichs, Bruno Dallagiovanna, Lucia Spangenberg

{"title":"Petri net modeling and simulation of post-transcriptional regulatory networks of human embryonic stem cell (hESC) differentiation to cardiomyocytes.","authors":"Aruana F F Hansel-Fröse, Christoph Brinkrolf, Marcel Friedrichs, Bruno Dallagiovanna, Lucia Spangenberg","doi":"10.1515/jib-2024-0037","DOIUrl":"10.1515/jib-2024-0037","url":null,"abstract":"Stem cells are capable of self-renewal and differentiation into various cell types, showing significant potential for cellular therapies and regenerative medicine, particularly in cardiovascular diseases. The differentiation to cardiomyocytes replicates the embryonic heart development, potentially supporting cardiac regeneration. Cardiomyogenesis is controlled by complex post-transcriptional regulation that affects the construction of gene regulatory networks (GRNs), such as: alternative polyadenylation (APA), length changes in untranslated regulatory regions (3'UTRs), and microRNA (miRNA) regulation. To deepen our understanding of the cardiomyogenesis process, we have modeled a GRN for each day of cardiomyocyte differentiation. Then, each GRN was automatically transformed by four transformation rules to a Petri net and simulated using the software VANESA. The Petri nets highlighted the relationship between genes and alternative isoforms, emphasizing the inhibition of miRNA on APA isoforms with varying 3'UTR lengths. Moreover, in silico simulation of miRNA knockout enabled the visualization of the consequential effects on isoform expression. Our Petri net models provide a resourceful tool and holistic perspective to investigate the functional orchestra of transcript regulation that differentiate hESCs to cardiomyocytes. Additionally, the models can be adapted to investigate post-transcriptional GRN in other biological contexts.","PeriodicalId":53625,"journal":{"name":"Journal of Integrative Bioinformatics","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12327202/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144334419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0