output
20082024
most citedPhen-Gen: combining phenotype and genotype to analyze rare disorders

155 citations

12 papers

q-bio.BM2024★ 95 cited

RiNALMo: General-Purpose RNA Language Models Can Generalize Well on Structure Prediction Tasks

Rafael Josip Penić, Tin Vlašić, Roland G. Huber +2

While RNA has recently been recognized as an interesting small-molecule drug target, many challenges remain to be addressed before we take full advantage of it. This emphasizes the…

cs.IT2024★ 3 cited

Gilbert-Varshamov Bound for Codes in Metric using Multivariate Analytic Combinatorics

Keshav Goyal, Duc Tu Dao, Mladen Kovačević +1

Analytic combinatorics in several variables refers to a suite of tools that provide sharp asymptotic estimates for certain combinatorial quantities. In this paper, we apply these t…

q-bio.PE2021★ 4 cited

Heterologous autoimmunity and prokaryotic immune defense

Hanrong Chen, Andreas Mayer, Vijay Balasubramanian

Some prokaryotes possess CRISPR-Cas systems that provide adaptive immunity to viruses guided by DNA segments called spacers acquired from invading phage. However, the patchy incide…

stat.ME2020★ 1 cited

A faster and more accurate algorithm for calculating population genetics statistics requiring sums of Stirling numbers of the first kind

Swaine L. Chen, Nico M. Temme

Stirling numbers of the first kind are used in the derivation of several population genetics statistics, which in turn are useful for testing evolutionary hypotheses directly from…

stat.ME2015★ 7 cited

Identification and Inference for Marginal Average Treatment Effect on the Treated With an Instrumental Variable

Lan Liu, Wang Miao, Baoluo Sun +2

In observational studies, treatments are typically not randomized and therefore estimated treatment effects may be subject to confounding bias. The instrumental variable (IV) desig…

q-bio.GN2015★ 155 cited

Phen-Gen: combining phenotype and genotype to analyze rare disorders

Asif Javed, Saloni Agrawal, Pauline C. Ng

We introduce Phen-Gen, a method which combines patient disease symptoms and sequencing data with prior domain knowledge to identify the causative gene(s) for rare disorders.