A new publication from our lab with Ki-Jo, Minseung, Iannis and Prof. Tagkopoulos on curating a Rheumatoid arthritis (RA) synovial genome-scale transcriptomic profiles which cover an intersection of 11769 genes from 11 datasets. Three clusters with different pathway signatures are observed and the prediction model using gene expression level as input for drug effectiveness are […]
The word2vec technique has become an essential part when building a text model and even adapted in other fields like building a recommendation system. In this blog, I will introduce the basic concepts and applications of word2vec. When building a machine learning model to understand text, the first challenge is to encode the text as […]
Metabolic Flux Analysis (MFA) is a technique used to quantify metabolic fluxes (the rate of turnover of molecules). MFA has at least two important applications: First, by studying metabolic flux, it is possible to adjust the amount of substrates/ingredients in the medium/protocol of cell culture [1] or mutate genes [2] to improve productivity. Second, by […]
Large-scale recombinant protein production is one of the most significant achievements of modern biotechnology. These proteins have wide applications in molecular biology, therapeutics, and industry. Efficient recombinant protein production using genetically manipulated organisms have saved several lives by providing the pure and accessible amount of therapeutic and prophylactic proteins. Today, more than 75 recombinant proteins […]
A new publication from our lab with Navneet, Linh, Minseung and Prof. Tagkopoulos on observing a reproducible phenomenon of abrupt population decrease followed by a rapid increase during long‐term chemostat cultivations in specific E.coli strains. Genetic basis of this phenomenon is identified by genome and transcription profiling. Rai, Navneet, et al. “Population collapse and adaptive rescue […]
A new publication from our lab with Ki-Jo and Prof. Tagkopoulos on reviewing different machine approaches for clinical data analysis in rheumatic diseases research. Kim, Ki-Jo, and Ilias Tagkopoulos. “Application of machine learning in rheumatic disease research.” The Korean journal of internal medicine(2018). doi:10.3904/kjim.2018.349 (link)
The threat of antibiotic resistance is well documented and frequently highlighted in the media, with constant mentions to “superbugs” and the potential end of effective antimicrobials. In the United States alone, over 2 million people become infected with antibiotic-resistant bacteria, and the death toll can reach 23,000 annually (1). In Europe, the estimations are that […]