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BioBam Joins BIOVALSA: Innovative Valorization of Plant Biomass Waste in Valencia for Functional Bioplastic Production

  We are proud to contribute to BIOVALSA, an initiative supported by the Instituto Valenciano de Competitividad e Innovación (IVACE+i). This collaboration unites leading Valencian organizations such as AIMPLAS, VIROMII, Prime Biopolymers, UPV, and BioBam. The project focuses on transforming agricultural residues—such as rice straw and citrus prunings—into high-value bioplastics like polylactic acid (PLA) and polybutylene succinate (PBS), used across

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BioBam at LongTREC meeting in Sweden

Our Teammate and PhD student Fabian Jetzinger, part of the LongTREC MSCA doctoral network, recently spent two months in Stockholm to collaborate with the developers of the isONpipeline tools. This pipeline, part of the OmicsBox Transcriptomics module, facilitates reference-free transcriptome reconstruction from Oxford Nanopore or PacBio long-read RNA sequencing data. Learning from their expertise and bringing in his own set

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OmicsBox in SEBiBC First Congress: End-to-end Single Cell Data Analysis Poster

  At BioBam we were thrilled to attend and sponsor the First Congress of Sociedad Española de Bioinformática i Biología Computacional (SEBiBC) in Valencia, a gathering of experts and researchers in bioinformatics and computational biology. Thanks to our colleague Marta Benegas, we had the opportunity to showcase our work advancing single-cell RNA sequencing (scRNA-Seq) analysis this year. Single-cell RNA sequencing

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OmicsBox 3.3 Release

BioinformaticsWe are excited to announce the release of OmicsBox 3.3, the All-In-One bioinformatics software, designed to simplify your research. This latest version integrates a range of new features and improvements, offering improved usability, advanced functionalities, and expanded database support to meet the diverse needs of the bioinformatics community. With a focus on providing powerful tools and resources, OmicsBox 3.3 brings

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Cutting-Edge Long-Read Transcriptomics Research Published in Nature Methods

We are pleased to announce the publication of a comprehensive study in Nature Methods: Systematic Assessment of Long-read RNA-seq Methods for Transcript Identification and Quantification. This research provides an in-depth evaluation of multiple long-read RNA sequencing technologies, comparing their effectiveness in transcript identification and quantification.BioBam participation in this research highlights its expertise in long-read sequencing technologies and its commitment to

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OmicsBox 3.2 Release

We are happy to announce the latest update of OmicsBox 3.2. “I am particularly happy to announce that with our latest release, our team managed to create a straightforward yet sophisticated solution for the challenging domain of Single Cell Transcriptomics. This marks a significant enhancement to the suite of complex analysis scenarios OmicsBox simplifies, including also Long-Read Transcriptomics, a field

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BioBam Achieves ISO 27001 Recertification

In recent years, we have been updating our ISO 27001 certification status since its initial achievement in 2020. Since then, the BioBam team has been dedicated to maintaining high standards of quality and security during each annual review. We are pleased to announce that BioBam has now been recertified as a secure and responsible organization by the ISO 27001 standard.

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BioBam Trip to PAG in San Diego

  The BioBam team has recently returned from the 31st International Plant and Animal Genome Conference (PAG) in sunny California. Once again, PAG proved to be a great place for sharing, learning, and presenting the latest features of our bioinformatics solutions.   We showed OmicsBox to many attendees and hopefully improved their understanding of its rich set of features and

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BioBam organizes Single-Cell Course

From September 27th to 29th, 2023, BioBam organized a Single-Cell Data Analysis Course as part of the Intercept-MDS Network Training Activities. The course was designed to offer a specialized educational program aimed at providing Ph.D. candidates within the network with essential skills for exploring the intriguing field of single-cell data analysis. Course Overview The three-day program immersed participants in the

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