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Biomedical subjects

Manish Kumar

Publications and source records attributed to Manish Kumar.

2 recordsLinked to original sources
PubMed2026

The Network of National COVID-19 Data Portals: public health equity through collaboration.

The network of the national COVID-19 Data Portals was developed and linked to the COVID-19 Data Portal (https://www.covid19dataportal.org/)inresponsetothe need for rapid data sharing and analysis during the 2020-2022 SARS-CoV-2 pandemic. Built on open-source code developed by the Swedish COVID-19 Data Portal (now the Swedish Pathogens Portal, www.pathogens.se) the network included 12 national portals addressing demand for local open data sharing and access, across data types and resources. It provides a robust case study of national initiatives for FAIR (Findable, Accessible, Interoperable and Reusable) resources and a foundation for future pandemic preparedness across pathogens globally. In this paper we outline the structure of the origins of the network of National COVID-19 Datal Portals, the technical aspects and code originating from the Swedish Portal and provide an overview of the services and tools offered by each Portal. The paper showcases the process and operation of four Portals: Sweden, Poland, Spain, Norway and The Netherlands. In this study, we observe that pandemic response greatly benefits from an established infrastructure that can be quickly mobilised, developed and extended. Collaborations and preparation built on solid foundations over several years, supported by investment in the form of national and international research grants, is key for sustainability, continuation and readiness to deploy such efforts.

COVID-19↗
PubMed2025

Metabolism and gene expression models for the microbiome reveal how diet and metabolic dysbiosis impact disease.

The gut microbiome plays a critical role in human health, spurring extensive research using multi-omic technologies. Although these tools offer valuable insights, they often fall short in capturing the complexity of microbial interactions that associate with disease onset, progression, and treatment. Thus, integration of multi-omics datasets with metabolic models is needed to predict associations between microbial activity and disease. Here, we automated the reconstruction of 495 metabolic and gene expression models (ME-models), overcoming the main limitation preventing the wide use of this approach. We integrated them with multi-omics data from patients with inflammatory bowel disease (IBD), identifying taxa associated with variations in amino acids, short-chain fatty acids, and pH in the gut of IBD patients. In general, this approach provides testable hypotheses of the metabolic activity of the gut microbiota, and the automated pipeline opens the opportunity to study microbial interactions in other biologically relevant settings using ME-models.

Humans↗