JIMB's core focus is technology-oriented and is distinct from, but entirely complementary to, the discovery science that currently dominates biomedicine. A main currency of JIMB is therefore the dissemination, open source or commercial, of technology innovations as useful products, with less emphasis on high profile discovery science papers. (Though those are nice too.)
JIMB is young and we're still growing, so watch this space as it picks up speed over the next year or two.
A sample of recent publications by JIMB scientists:
- Noah Spies, et. al (2017) Genome-wide Reconstruction of Complex Structural Variants Using Read Clouds. Nature Methods. doi:10.1038/nmeth.4366
- Lindsay K. Vang, et. al (2017) Preparation of a Set of Total RNA Benchmarking Samples for Performance Assessment of Genome-scale Differential Gene Expression. NIST Special Publication 1200-23
- Ariel Hecht, et. al (2017) Measurements of translation initiation from all 64 codons in E. coli. Nucleic Acids Research. https://doi.org/10.1093/nar/gkx070
- Noah Spies, et. al (2016) Genome-wide Reconstruction of Complex Structural Variants Using Read Clouds. bioRxiv.
- John T. Elliot et. al (2016) Toward Achieving Harmonization in a Nano- cytotoxicity Assay Measurement through an Interlaboratory Comparison Study. Altex http://dx.doi.org/10.14573/altex.1605021
- Ariel Hecht et. al (2016) Measurements of Translation Initiation from all 64 Codons in E.Coli. bioRxiv Pre-Print.
- Jeff Glasgow et. al (2016) In Vivo Site-Specific Protein Tagging with Diverse Amines Using an Engineered Sorties Variant. Journal of the American Chemical Society. pp 7496–7499
- Peter F. McLean et. al (2016) Characterizing the Non-Normal Distribution of Flow Cytometry Measurements from Transiently Expressed Constructs in Mammalian Cells . bioRxiv.
- Ariel Hecht et. al (2016) When Wavelengths Collide: Bias in Cell Abundance Measurements Due to Expressed Fluorescent Protein. ACS Synthetic Biology. PP5, 1024-1027
- P. Scott Pine et. al (2016) BioMed Central Publication: Evaluation of the External RNA Controls Consortium (ERCC) reference material using a modified Latin square design.BMC Biotechnology DOI: 10.1186/s12896-016-0281-x
- Justin Zook et. al (2016) Extensive sequencing of seven genomes to characterize benchmark reference materials. Scientific Data Publication: Article Number 160025
- Rachel L. Goldfeder et. al (2016) Medical implications of technical accuracy in genome sequencing DOI 10.1186/s13073-016-0269-0
- Russ B. Altman et. al A research roadmap for next-generation sequencing informatics Science Translational Medicine. Vol 8 Issue 335 335ps10
- Summon Sardar et. al (2016) Roles of Nanofiber Scaffold Structure and Chemistry in Directing Human Bone Marrow Stromal Cell Response MedCrave. Volume 1 Issue 1
- Hangnoh Lee et. al (2016) External RNA Controls Consortium Beta Version Update Journal of Genomics pp 4: 19-22
- Hemang Parikh et. al (2016) svclassify: a method to establish benchmark structural variant calls BMC Genomics. DOI 10.1186/s12864-016-2366-2
- S.M. Da Silva et. al (2016) Evaluation of microbial qPCR workflows using engineered Saccharomyces cerevisiae Elsevier pp 27–33
- Anil Patwardhan et. al (2015) Achieving high-sensitivity for clinical applications using augmented exome sequencing BioMed Central DOI 10.1186/s13073-015-0197-4
- Justin Zook et. al (2015) Advancing Benchmarks for Genome Sequencing. Cell Press pp 176-177
- Amy S Gargis et. al (2015) Good laboratory practice for clinical next-generation sequencing informatics pipelines Nature Biotechnology pp 689-693
- Russ B. Altman et. al (2015) Unmet needs: Research helps regulators do their jobs. Science Translational Medicine. Vol 7 Issue 315 315ps22
- Noah Spies, et. al (2015) svviz: a read viewer for validating structural variants. Oxford University Press
- Steven J. Mack et. al (2015) Minimum information for reporting next generation sequence genotyping (MIRING): Guidelines for reporting HLA and KIR genotyping via next generation sequencing Human Immunology pp 954-962
- Jerod Parsons et. al (2015) Using mixtures of biological samples as process controls for RNA-sequencing experiments. BMC Genomics DOI 10.1186/s12864-015-1912-7
- Nathan Olson et. al (2015) PEPR: pipelines for evaluating prokaryotic references Anal Banal Chem DOI 10.1007/s00216-015-9299-5
- Matthias Rossleinet et. al (2014) Use of Cause-and-Effect Analysis to Design a High-Quality Nanocytotoxicology Assay. Chemical Research in Toxicology pp 21-30