Browsing Faculty of Arts and Sciences by Keyword "Computational biology"
Now showing items 1-7 of 7
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Bayesian Models to Identify Hidden Patterns with Applications in Biology
(2022-08-08)Technology advances have made possible the generation of massive amounts of data in biology. For example, whole genome sequencing (WGS) has made available (nearly) the entirety of DNA sequences of various organisms. ... -
Development and validation of computational models for efficient design of biological sequences
(2022-01-10)There is a huge surge of interest in designing a wide variety of proteins to use as molecular research tools and biotherapeutics - promising to revolutionize our capacity to design what we need at will. This is particularly ... -
Differential Gene and Transcript Expression Analysis of RNA-seq Experiments with TopHat and Cufflinks
(Nature Publishing Group, 2012)Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments ... -
Large language models for biological prediction and design
(2024-01-25)Predicting the functional impact of changes to biological sequences is a central challenge in genetics and biology. Beyond genetics, sequence-to-function mapping has key applications in the design of sequences for use as ... -
Mapping the Fitness Landscape of Gene Expression Uncovers the Cause of Antagonism and Sign Epistasis between Adaptive Mutations
(Public Library of Science, 2014)How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial ... -
Metabolic Erosion Primarily Through Mutation Accumulation, and Not Tradeoffs, Drives Limited Evolution of Substrate Specificity in Escherichia coli
(Public Library of Science, 2014)Evolutionary adaptation to a constant environment is often accompanied by specialization and a reduction of fitness in other environments. We assayed the ability of the Lenski Escherichia coli populations to grow on a range ... -
Quantitative analysis of dynamic tumor cell phenotypes regulated by tumor associated macrophages.
(2021-07-12)Cancer cells and the tumor microenvironment (TME) dynamically interact to promote cancer progression. One such cell type demonstrated to create an immunosuppressive TME are tumor-associated macrophages (TAMs). Furthermore, ...