Characterizing the genetic structure of large cohorts has become increasingly important as
genetic studies extend to massive, increasingly diverse biobanks. Popular methods …

With the recent advances in machine learning for quantum chemistry, it is now possible to
predict the chemical properties of compounds and to generate novel molecules. Existing …

Advances in single-cell RNA sequencing (scRNA-seq) have led to successes in discovering
novel cell types and understanding cellular heterogeneity among complex cell populations …

The use of multi-mode remote sensing data for biomass prediction is of potential value to aid
planting management and yield maximization. In this study, an advanced biomass …

Kelompok yang rentan terserang penyakit adalah kelompok anak-anak, yang memiliki
permasalahan Kesehatan terutama sejak usia dini. Penyakit yang sering terjadi pada …

Biopharma drug discovery requires a set of approaches to find, produce, and test the safety
of drugs for clinical application. A crucial part involves image-based screening of cell culture …

Considering smooth mappings from input vectors to continuous targets, our goal is to
characterise subspaces of the input domain, which are invariant under such mappings …

The ability to find and recognize patterns in high-dimensional geophysical data is
fundamental to climate science and critical for meaningful interpretation of weather and …

Characterizing the genetic substructure of large cohorts has become increasingly important
as genetic association and prediction studies are extended to massive, increasingly diverse …

We introduce a novel exploratory technique, termed biarchetype analysis, which extends
archetype analysis to simultaneously identify archetypes of both observations and features …