Article processing charges (APCs) support peer review coordination, editorial management, production, DOI registration, and long term digital archiving. APCs are applied after acceptance and do not influence editorial decisions.

JBD is committed to transparency and affordability for authors in diabetes bioinformatics communities.

• Editorial assessment and peer review management
• Copyediting, layout, and publication production
• DOI registration and metadata validation
• Long term archiving and platform maintenance
• Open access hosting and global dissemination

Authors from World Bank classified low income and lower middle income countries may be eligible for partial APC waivers. Requests are evaluated on a case by case basis and must be submitted before acceptance.

Membership options offer discounted APCs for eligible authors and institutions. Contact the editorial office for guidance.

Many diabetes research teams publish under grant or institutional mandates. Share funder requirements early so the editorial office can align invoicing and reporting needs.

• Provide grant identifiers and funding statements
• Confirm open access mandates or repository requirements
• Share billing contacts for institutional or funder payments
• Document any reporting deadlines tied to publication

To avoid delays, payments should be completed within 48 hours of invoice receipt. Publication proceeds after payment confirmation.

• If your institution requires invoice language or grant identifiers, provide them before acceptance to avoid delays.
• APC receipts include journal name, manuscript title, and DOI reference for institutional reporting.
• Payment can be made by institutions, funders, or authors. Coordinate billing details early to streamline processing.
• Requests for partial waivers should be submitted before acceptance with supporting documentation.
• APCs support long term digital preservation and open access distribution of diabetes bioinformatics research.
• If a funding agency requires open access confirmation, the editorial office can provide verification after publication.
• Invoices can be issued to a central grants office when funding sources require consolidated billing.
• APC questions are handled by the editorial office; contact them early to align budgets with publication timelines.
• Provide billing contacts and purchase order details early to avoid administrative delays during production.
• Institutions covering APCs should confirm currency conversion requirements and tax exemptions if applicable.
• Waiver requests should include a brief justification and confirmation of eligibility criteria.
• If funding is pending, notify the editorial office so invoice timelines can be coordinated.
• Payment confirmations are required before copyediting and proof preparation begin.
• For multicenter studies, designate a single billing contact responsible for APC coordination.
• Describe cohort selection, inclusion criteria, and diabetes phenotype definitions so readers understand the population context.
• Provide metadata about biospecimens, including collection timing relative to treatment, fasting status, and storage conditions.
• Report preprocessing steps for sequencing or omics data, including alignment tools, reference genomes, and quality thresholds.
• Include normalization approaches for multi-omics integration, such as batch correction or scaling methods.
• Clarify how missing data were handled, especially in longitudinal or wearable datasets.
• Provide version numbers for software, libraries, and pipelines to support reproducibility.
• Report performance metrics for predictive models, including calibration, discrimination, and external validation results.
• Explain feature selection strategies and how overfitting risks were mitigated.
• Describe cross validation or train test splits and confirm that data leakage was avoided.
• Share accession numbers or repository links for public datasets and code when possible.
• Provide a concise data availability statement that notes any access restrictions for sensitive clinical data.
• Report ethical approvals and consent procedures for human datasets or biobanks.
• Include clinical context for diabetes subtypes, such as type 1, type 2, gestational, or secondary diabetes.
• Define glycemic metrics clearly, including HbA1c, fasting glucose, or continuous glucose monitoring summaries.
• Describe how comorbidities or medications were accounted for in the analysis.
• If using wearable or digital health data, report device validation and sampling frequency.
• Provide details on integration of electronic health records, including coding systems and quality checks.
• Discuss limitations related to population bias, data sparsity, or missing clinical covariates.
• Explain interpretability methods used for machine learning models and their clinical relevance.
• Report sensitivity analyses that test robustness across cohorts or subgroups.
• Describe how class imbalance was addressed in predictive models for complications.
• Clarify computational resource requirements and runtime considerations for large scale analyses.
• Provide standard evaluation metrics for clustering or stratification analyses.
• If biomarkers are proposed, describe validation evidence and biological plausibility.
• Explain how multi-site data were harmonized and how site effects were controlled.
• Include quality control plots or summary statistics for omics data.
• Describe how data sharing aligns with FAIR principles when possible.
• Provide documentation for custom scripts or pipelines that are not publicly available.
• Highlight reproducibility steps such as containerization or workflow managers.
• Report how model thresholds were selected for risk prediction tools.
• If synthetic data are used, describe generation methods and validation checks.
• Discuss how genomic variants were annotated and interpreted in a diabetes context.
• Provide evidence for clinical utility, such as decision impact or workflow integration.
• Explain how uncertainty was quantified for model outputs and predictions.
• Describe how longitudinal trajectories were modeled for glycemic control or complications.
• Include a short statement on limitations and future validation needs.
• Provide clear definitions for endpoints like incident diabetes or remission.
• If imaging data are used, report acquisition parameters and analysis software.
• Clarify how multi-ethnic representation was handled and reported.

JBD is committed to rigorous, transparent publishing in bioinformatics and diabetes research. We emphasize reproducible computational methods, clear data provenance, and ethical compliance across all article types.

The editorial office supports authors, editors, and reviewers with clear guidance and responsive communication. For questions about scope or workflow, contact [email protected].

We encourage continuous improvement in reporting practices and share updates that help the community maintain high standards in computational and translational diabetes research.