Avantika Lal

Oct 14, 2024 | biorxiv.org | Avantika Lal |Alexander Karollus |Laura M Gunsalus |David Garfield

AbstractSequence-to-function models that predict gene expression from genomic DNA sequence have proven valuable for many biological tasks, including understanding cis-regulatory syntax and interpreting non-coding genetic variants. However, current state-of-the-art models have been trained largely on bulk expression profiles from healthy tissues or cell lines, and have not learned the properties of precise cell types and states that are captured in large-scale single-cell transcriptomic datasets.

Sep 22, 2024 | biorxiv.org | Avantika Lal |Laura M Gunsalus |Surag Nair |Tommaso Biancalani

AbstractDeep learning models are increasingly being used to perform a variety of tasks on DNA sequences, such as predicting tissue- and cell type- specific sequence activity, deriving cis-regulatory rules, predicting non-coding variant effects, and designing synthetic regulatory sequences. However, these models require specialized knowledge to build, train and interpret correctly.

May 16, 2024 | biorxiv.org | Avantika Lal |Laura M Gunsalus |Anay Gupta |Tommaso Biancalani

AbstractThe design of regulatory elements is pivotal in gene and cell therapy, where DNA sequences are engineered to drive elevated and cell-type specific expression. However, the systematic assessment of synthetic DNA sequences without robust metrics and easy-to-use software remains challenging.

Feb 18, 2024 | biorxiv.org | Avantika Lal |David Garfield |Tommaso Biancalani |Gökcen Eraslan

AbstractCis-regulatory elements (CREs), such as promoters and enhancers, are DNA sequences that regulate the expression of genes. The activity of a CRE is influenced by the order, composition and spacing of sequence motifs that bind to proteins called transcription factors (TFs). Synthetic CREs with specific properties are needed for biomanufacturing as well as for many therapeutic applications including cell and gene therapy.

Nov 27, 2023 | biorxiv.org | Avantika Lal |Laura M Gunsalus |Tommaso Biancalani |Anay Gupta

AbstractThe design of regulatory elements is pivotal in numerous therapeutic interventions, including gene and cell therapy, wherein the typical objective is to engineer DNA sequences exhibiting specific attributes like cell-type specificity and elevated expression levels. However, the systematic assessment of these constructed DNA sequences remains challenging due to the absence of robust metrics and an integrated software framework.