Full text
2,353 characters
· extracted from
oa-doi-fallback
· click to expand
Abstract
Disparities in formal bioinformatics training exacerbate the global skills gap, impeding the democratized application of advanced genomic technologies. To bridge this divide, we introduce a scalable, hybrid training framework designed to rapidly accelerate regional bioinformatics capacity. We exemplify this approach through the Eastern European Bioinformatics and Genomics (EEBG) workshop series — a cross-disciplinary initiative that pairs international faculty with local institutions to deliver modular, hands-on curricula. Functioning as a structured knowledge-transfer pipeline, the series has catalyzed a sustainable educational ecosystem, evidenced by the establishment of multiple independent summer schools across the region. The assessment of the 2025 EEBG workshop in Kraków, Poland, validates the model’s viability; participant metrics confirm high efficacy in skill acquisition (mean satisfaction: 4.4/5.0) and community building. Crucially, the hybrid delivery mode dismantled geographic barriers, serving as a vital mechanism for maintaining scientific continuity for researchers facing displacement and crisis. Synthesizing these outcomes, we define the core features of a replicable blueprint for scientific readiness in resource-constrained environments. We conclude by presenting a strategic roadmap — organized around infrastructure standardization, governance sustainability, and geographical expansion — for adapting this regional proof-of-concept into a global export-ready model, offering a critical path toward ensuring universal access to genomic innovation.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Email: oleksyk{at}oakland.edu, daryna.yakymenko{at}student.uj.edu.pl, s.bozek{at}sanoscience.org, viorel.munteanu{at}lt.utm.md, wojtek.pilch{at}uj.edu.pl, zoia.comarova{at}gmail.com, victor.gordeev{at}student.usv.ro, gboldirev1{at}student.gsu.edu, dumitru.ciorba{at}fcim.utm.md, viorel.bostan{at}adm.utm.md, chm2042{at}med.cornell.edu, agl4001{at}med.cornell.edu, nadiia.kasianchuk{at}gmail.com, nishchenkodaria{at}gmail.com, vpopic{at}broadinstitute.org, andrei.lobiuc{at}usm.ro, mcovasa{at}usm.ro; mihai.covasa{at}belmont.edu, HoelzerM{at}rki.de, joanna.polanska{at}polsl.pl, alexz{at}cs.gsu.edu, vasili.braga{at}ati.utm.md, dimian{at}usm.ro, pawel.labaj{at}uj.edu.pl
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.