Journal of Integrative Bioinformatics整合生物信息学杂志
Journal of Integrative Bioinformatics(英文缩写 J INTEGR BIOINFORMAT),ISSN 1613-4516,eISSN 1613-4516,中文译名:整合生物信息学杂志 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-10-01 至 2026-09-30，按本站收录文献的发表日期统计。
期刊介绍
Journal of Integrative Bioinformatics 最新收录文献
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1. A standardized SBML/PRISM benchmark library for stochastic model checking in synthetic biology.
PMID:日期:2026-09-02Stochastic model checking is a powerful verification technique used in engineering to assess system reliability and correctness. Many synthetic biological systems, including chemical reaction networks, can be modeled as stochastic processes, making stochastic model checking well suited for evaluating and improving their performance. However, direct application in synthetic biology faces domain-specific challenges that often require adapting existing analysis techniques and developing new algorithms that scale to biological complexity. To support this software development, we present a curated library of case studies representing biologically inspired stochastic models with unbounded state spaces. Each case study is provided in both SBML and PRISM formats to support accessibility and interoperability. By openly releasing the library and encouraging community contributions, this work aims to improve reproducibility, enable meaningful tool comparisons, and accelerate development of robust software infrastructure for stochastic model checking in synthetic biology.
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2. SBOL converter: enabling backward compatibility for biological designs.
PMID:日期:2026-08-18The Synthetic Biology Open Language (SBOL) is a community-driven and machine-readable standard for creating and sharing biological designs. SBOL has evolved over the years, resulting in three major versions, each introducing new features. Although SBOL3 is the latest community-adopted version, it has not been fully integrated into software tools and repositories due to the lack of essential libraries to facilitate this transition. In this paper, we present the SBOL Converter, a backward-compatibility tool that can update legacy designs to the latest SBOL version. Designs can also be converted to previous versions to allow legacy tools to be used in ongoing projects. Moreover, it incorporates existing SBOL tools, providing a unified interface to orchestrate the validation of designs and checking against various compliance rules and best practices. The converter can also process other popular biological formats such as GenBank and FASTA. As a lightweight tool, it can be integrated into engineering biology design workflows to accelerate tool development and enable the transition to the latest versions as they are released, facilitating the reusability and reproducibility of biological designs.
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3. The DSMZ Digital Diversity Annotation Hub: a pipeline for database expansion via text mining and human curation.
PMID:日期:2026-08-17Maintaining scientific databases that depend on continuous curation of research literature often requires labor-intensive, slow, and error-prone annotation processes. To address these challenges, we present a pipeline that integrates text mining with expert supervision to support database expansion. Using the BRENDA enzyme database as a case study, we compiled a relation extraction dataset by aligning document-level annotations with literature references through distant supervision. We then developed a neural model that performs entity recognition and relation classification, enabling the extraction of enzyme-strain associations from full-text articles. To close the loop between machine learning and expert curation, we designed a web-based interface that allows annotators to review and refine predicted relations. While preliminary, our initial experiments show the potential of combining weak supervision and human-in-the-loop validation to accelerate the integration of literature-derived information into knowledge bases.
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4. The parameter estimation tables (PEtab) format version 2.
PMID:日期:2026-08-13Parameter estimation is a central task in data-driven computational modeling, and a clear, unambiguous, and commonly understood specification of parameter estimation problems is essential for reproducibility and interoperability. PEtab provides a standardized framework for defining such problems in systems biology and systems medicine, particularly for ordinary differential equation models. This document describes the second version of the PEtab format, PEtab 2.0. PEtab 2.0 simplifies and clarifies how estimation problems are defined, while also extending the standard to support more complex and realistic experimental setups. Key improvements include support for additional model formats beyond SBML, expanded and improved specification of parameter priors for Bayesian parameter estimation, and a more flexible description of experiments that allows multiple conditions, time periods, and pre-equilibration steps within a single simulation. Additional updates refine the definition of model parameters, measurement noise, and observation models, and remove ambiguous or confusing features from earlier versions. Version 2 also includes a general extension mechanism, to add functionality for specialized applications not covered by the core standard.
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5. SBML level 3 package: flux balance constraints version 3.
PMID:日期:2026-08-13Constraint-based modeling is a well-established modeling methodology used to study biological networks at both the medium-scale and genome-scale. Due to their large size and complexity, such steady-state flux models are typically analyzed using constraint-based optimization techniques, such as Flux Balance Analysis (FBA). The Flux Balance Constraints (FBC) Package extends SBML Level 3 to provide a standardized format for encoding, exchanging, and annotating constraint-based models. It includes support for modeling concepts such as objective functions, flux bounds, and annotation of model components that facilitate reaction balancing. Version two extended the original release by adding support for encoding gene-protein associations. Version three builds upon and maintains backwards compatibility with Version two by introducing new elements and attributes that include: user-defined constraints, a new quadratic variable type and key-value pair annotation that can be used to store additional information relevant to constraint-based modeling. The only changes to existing attributes are that a Species charge is no longer restricted to an integer value and chemicalFormula can now include generic components. In addition to providing the elements necessary to uniquely encode constraint-based models, the FBC package provides an open platform that facilitates the continued, cross-community development of an interoperable, constraint-based model encoding format.
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6. Pithos - a scalable and secure data container for FAIR-compliant research data management in life sciences.
PMID:日期:2026-08-12Modern research techniques have led to exponential growth in the volume and complexity of scientific data. Consequently, managing these volumes securely and efficiently has become a major challenge. While all research domains face these challenges, life science research is particularly affected because current approaches often rely on a large set of different file formats, with metadata stored in separated databases or spreadsheets. This leads to fragmented datasets, orphaned data, and compromised research reproducibility. Traditional solutions also force researchers to choose between security and accessibility, with encrypted files preventing selective access and indexed formats lacking adequate security for sensitive data. These limitations are particularly problematic in large-scale genomic studies where researchers must decompress multi-gigabyte files to access specific regions, creating computational bottlenecks and inefficient network usage when working with cloud-stored datasets. We introduce Pithos, a next-generation file format specifically designed for scientific data management in distributed cloud environments. The format uses content-defined chunking to enable efficient deduplication across distributed storage systems, thereby reducing storage costs and bandwidth requirements. The append-only structure ensures data immutability and allows for incremental updates without compromising content. Benchmark results show that Pithos outperforms existing solutions in read and write performance, with comparable or improved storage efficiency.
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7. Advancing cross-domain integration and semantic technologies: proceedings of the 19th international symposium on integrative bioinformatics.
PMID:日期:2026-08-11This special issue of the presents proceedings from the 19th International Symposium on Integrative Bioinformatics, which was held 10-12 September 2025. The featured contributions address critical bottlenecks in life science data management, specifically focusing on the practical implementation of FAIR (Findable, Accessible, Interoperable, and Reusable) principles as an essential prerequisite for data integration and data interoperability. Comprising nine peer-reviewed articles, the issue highlights methodological advancements in cross-omics integration, semantic technologies for machine interpretability, and the deployment of robust digital infrastructures like RO-Crate. By bridging technical innovation with community-driven data stewardship, this collection provides actionable frameworks to modernize the research data lifecycle and ensure computational reproducibility across the life sciences.
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8. Fusion of computational and experimental provenance in RO-Crate.
PMID:日期:2026-07-06Modern research projects typically involve several measurement techniques and computational analyses, resulting in complex, multimodal research data objects. While the FAIR Principles provide a framework for making data Findable, Accessible, Interoperable, and Reusable, researchers must still apply community standards for each data type, where available. This challenge is particularly pronounced in computational analyses and workflows, where high methodological diversity makes it difficult to create meaningful FAIR Digital Objects that also capture experimental provenance. Such objects must describe the full research process by interlinking experimental and computational steps in a unified, queryable provenance model. The ISA framework captures laboratory protocols and processes, while computational analyses are described using workflow-centric models such as Workflow (Run) RO-Crate, which separate workflow definitions from execution traces. Despite conceptual similarities, these approaches remain largely disconnected. This paper presents the ARC Workflow Run RO-Crate profile, which aligns ISA-based experimental provenance with computational workflow and execution metadata in a single, standards-compliant container. It enables shared semantics and makes experimental assays and workflow runs interoperable within a coherent provenance graph interpretable by both ISA- and workflow-aware tools. At the same time, the profile harmonizes experimental and computational provenance and remains compatible with existing (Workflow) RO-Crate and ISA tooling ecosystems.
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9. Updates and validation of the Compi RNA-seq pipeline with a case study in Alzheimer's disease.
PMID:日期:2026-06-17RNA-seq data analysis is a multi-step process that typically includes demultiplexing, alignment to the reference genome, read counting and genome annotation, ultimately leading to differential expression analysis (DEA). Several pipelines are currently available to support these steps and produce outputs adapted to specific experimental needs. Such pipelines must also ensure reproducibility, offer user-friendly implementation, support the analysis of complex genomes, allow batch correction, and remain sufficiently flexible to enable customization. Here , we present version 2.2 of a fully customizable command-line RNA-seq pipeline, developed within the Compi framework through the conversion and extension of the previously established DEWE graphical user interface tool. This updated version includes tasks for FASTQ quality control, two alternative read-counting strategies, and recently developed tools for DEA and pathway analysis, such as DElite and RCPA. Furthermore, we apply the pipeline to an exploratory RNA-seq study comparing transcriptomic profiles of Alzheimer's disease (AD) patients with healthy controls (HC) to identify putative disease molecular signatures and assess the pathways affected by the disease.
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10. Fragment-level FAIRness: annotating scientific data and its provenance using data fragment selectors.
PMID:日期:2026-06-17Scientific communication depends on the production of (findable, accessible, interoperable, reusable) data. Yet when datasets are shared, they remain hard to interpret across domains because annotations are tied to heterogeneous file formats and implicit semantics. We present a method for annotation based on : -addressable pointers to sub-file regions (e.g., CSV rows/columns, JSON objects) whose meaning is defined by an accompanying explicit selector standard. DFS are aggregated into a , a lightweight schema that binds referenced fragments to -backed semantics, including units and object types. Separating structural addressing from semantic interpretation enables reusable schemas and robust automation without format-specific parsing. To support provenance annotation, we integrate DFS with the Investigation-Study-Assay () metadata model, extending data-entity references to enable . We realize the model in two interoperable serializations: for spreadsheet-centric practice and an Research Object Crate Datamap profile for web-native packaging and exchange. These specifications deliver : precise, links between process metadata and the data portions they describe. We demonstrate practical applicability by introducing a specification, providing a standardized workflow for annotating aggregated supplementary data in journal publications, and via programmatic exploration of a real-world proteomics project.