A new publication from our lab with Navneet, Linh, Minseung and Prof. Tagkopoulos on a new reproducible phenomenon on chemostat cultivation, where the population collapses around 100h and it recovers through adaptive mutations in key membrane and tRNA genes. Rai, Navneet, et al. “Population collapse and adaptive rescue during long‐term chemostat fermentation.” Biotechnology and bioengineering 116.3 (2019): […]
A new publication from our lab with Ameen and Prof. Tagkopoulos on novel neural network structure (Genetic Neural Network, GNN) which achieve 40% more accurate than other conventional architectures (MLP, RNN, BiRNN) on average for gene expression level predictions. Eetemadi, Ameen, and Ilias Tagkopoulos. “Genetic Neural Networks: an artificial neural network architecture for capturing gene […]
The concept of “garbage in–garbage out” applies when building a data-driven predictive model. The time for training a model increase exponentially with the number of features. Too many features also becomes a hurdle when attempting to select meaningful features. Moreover, the risk of overfitting increases as the number of features increases given limited number of […]
Short answer: Knowledge graph completion is the act of inferring new edges, called facts, in a knowledge graph based on the already existing relational data. Understanding this will require explanation of two concepts, notably 1) what knowledge graph is, and 2) what knowledge graph completion is. For clarity, use of the term “knowledge graph” here is […]
From comedy shows to everyday conversation, humor plays an important part in human interaction, whether it’s used to expedite courtship or enhance social bonding. And yet, if asked why we find certain things funny many of us will often struggle to express the reason. For something so prevalent in our daily lives, it is certainly […]
A well-defined transfer learning approach is desirable in computational biology field, as it allows us to learn better in a specific field by utilizing the knowledge in related fields. However, this approach is not trivial at all, and so far there are some notable challenges in applying transfer learning in biological data: Different biological features […]
Our lab member Navneet Rai presented a poster describing the characterization of microbial anticipatory responses in the mammalian gut at the International Conference on Microbiome Engineering.
There are many choices and assumptions to make when designing a machine learning (ML) based system. Taking the common choice is appealing but can undermine your system performance. Having recently designed an ML based system for prediction of gene expression (GE) [1], we made various uncommon but sensible choices and assumptions given the particular problem […]
Navneet Rai’s “Predicting evolution of microbial communities under stress” poster wins the Best Poster Award at the UC Davis Genome Center Halloween Symposium!
Emergence of antibiotic resistance bacteria is one major problem of the modern era. Bacteria are developing resistance against antibiotics at alarming rate and we are running out of effective antibiotics. Bacteria deploy several short- and long-term adaptive strategies to counteract the effect of potent antibiotics. Short-term strategies include pumping out drugs using multi drug efflux […]