Is Big Data a real problem in biopharma sector or is it the lack of tools to systematically extract meaningful information from biological datasets? Check our article magazine and give us feed-back! bioprocessintl.com/manufacturing/…

Take a look at our perspective paper highlighting the key aspects restraining the routine implementation of metabolic tools in biopharma industry #ProcessSystemsBiologyandEngineeringTeam #GSK nature.com/articles/s4154…

Knocking out 14 proteins in CHO cells improved recombinant protein drug amount and purity jacobsschool.ucsd.edu/news/news_rele…

MEDUSA is a software package developed by Greg Medlock with help from Tom Moutinho to develop #ensembles of metabolic #network reconstructions for #COBRA modeling and analysis. #PLOSCompBio dx.plos.org/10.1371/journa…

Can we identify all of the cell machinery needed to make and secrete a therapeutic protein? See our latest preprint where we used BioID to map the protein-protein interactions of a panel secreted plasma protein drugs. by @MojtabaSamoudi Caressa Robinson biorxiv.org/cgi/content/sh…

I recently came across Meta : a platform performing big data analysis on scientific papers... a step towards a fully machine readable scientific knowledge database ?

Cell-type and tissue specific metabolic models are often missing many housekeeping genes. New paper out from Chintan Joshi presents a method that effectively retains them. doi.org/10.1371/journa…

I really like this paper. They have a detailed model of metabolism which becomes the input for an ML prediction an opaque process we are still struggling to model (glycan biosynthesis). Thanks for this awesome work @KontoravdiC & Pavlos Kotidis ! doi.org/10.1016/j.mec.…

Probably making its way around twitter, but Albert Liang, a student in my lab, shared this with me #ShutDownAcademia

An amazing *randomized trial* on Twitter+academia: 112 papers were randomly chosen to be shared on twitter by a group with ~58k followers or to not be shared. Papers that were tweeted accumulated 4x more citations compared to non-tweeted papers over 1yr. pubmed.ncbi.nlm.nih.gov/32504611/

A variety of assumptions and parameters go into genome-scale mammalian metabolic models. Which ones are the most important? See our new preprint @Matt_schinn doi.org/10.1101/2020.0…

Human milk is full of complex carbohydrates linked to infant health and development, but it's still unclear how they are made. Ben Kellman bkell1123.bsky.social and Anne Richelle led a multi-omics data integration effort to decipher how they are synthesized in the mother. preprint doi.org/10.1101/2020.0…

Biopharmaceutical-producing cells need careful feed control, but it is difficult to rapidly measure nutrients for optimal drug production. Matt and Pfizer Inc. leveraged genome-scale metabolic modeling and machine learning to predict nutrient needs doi.org/10.1101/2020.0…

Exciting new postdoc opening at UCSD lewislab.ucsd.edu/join-us/ to analyze large amounts of diverse data re: #autism (e.g., genetics, RNA-seq, clinical data, imaging). Building off of our recent exciting work doi.org/10.1101/2020.0… cell.com/trends/neurosc… nature.com/articles/s4159…

Free workshop to explore how cross-disciplinary systems thinking approaches can be applied to the development of regenerative medicine products where I will be discussing the "Adoption of metabolic modeling tools in biopharmaceutical industry" nationalacademies.org/event/10-22-20…

Cell-cell interactions are crucial for multicellular life. In this preprint we inferred the spatial code embedded in the molecular interactions across the whole body of C. elegans. We integrated single cell RNA-seq, ligand-receptor pairs and cell location. biorxiv.org/content/10.110…

Pathway enrichment is useful and ubiquitous in omics analysis. But can we similarly quantify changes in cell functions, by analyzing omics in systems biology model outputs? Check out CellFie by Anne Richelle, now in Cell Reports Methods: doi.org/10.1016/j.crme… and in GenePattern

The facility of the future will feature intensified, continuous, predictive, and autonomous biomanufacturing. Join us in this breakout session to get a glimpse of how digital transformation will shape the industry. ow.ly/Z8FL50GtLc2