David Kainer

FLASH-P constructs causal regulatory networks from literature, predicting perturbation outcomes with 90% accuracy across seven species.

The paper uses spatial transcriptomics to investigate the spatial expression of C4 photosynthesis-related genes in wheat grain, finding tissue-specific expression patterns that support the C4 wheat hypothesis.

The paper uses long-read sequencing to analyze telomere-to-telomere assemblies in Populus trichocarpa, revealing complex KCS gene variation and its association with helitron transposons.

This study uses spatial transcriptomics to map gene expression in developing wheat seeds, revealing radial patterns in the endosperm and subgenome bias in key genes.

RWRtoolkit enables multi-omic network analysis using random walks on multiplex networks across any species, providing tools for topological analysis and statistical evaluation.

This study uses Large Language Models with Retrieval-Augmented Generation to auto-annotate plant phenotypes with ontology terms, achieving results comparable to expert annotations.

This study identifies chromosomal inversions in mango genomes and shows they accumulate both deleterious and favorable loci, impacting breeding traits.

The paper investigates how chromatin modification and genomic structural variants contribute to neurodevelopment and autism spectrum disorder by analyzing multiomic data.

The paper introduces network analysis methods to identify exogenous compounds that trigger specialized metabolite production in fungi and distinguish unknown analytes.

This paper develops a novel feature set and public resource for predicting CRISPR-Cas9 sgRNA efficiency using quantum chemical tensors and explainable-AI methods.

The paper uses exascale computing to generate high-resolution global geoclimate zones by clustering environmental similarity data from 71 variables over 50 years.

This study relaxes GWAS significance thresholds and uses GRIN to identify additional genes linked to suicidal behavior, which replicate across cohorts and show stronger biological connections.

The paper identifies structural variants (SVs) in ASD families and links them to molecular pathways and genes associated with non-verbal ASD, using explainable AI for subgroup identification.

This paper presents the first hybrid assembled genome of Eucalyptus polybractea using short- and long-read sequencing, achieving high contiguity and completeness.

The paper uses a systems biology approach to analyze COVID-19 data and identifies non-respiratory infection pathways as key to its global spread.

The paper estimates the somatic mutation rate in a long-lived Eucalyptus tree using a novel method, finding it lower per unit of growth compared to Arabidopsis.

The paper presents a draft genome assembly of Eucalyptus pauciflora using long and short-read data and evaluates four assemblers to identify the best assembly.

The paper evaluates chloroplast genome assembly methods using Eucalyptus pauciflora, finding that hybrid long- and short-read assemblies are most accurate.

The paper presents an open-source workflow for establishing MinION long-read sequencing in any laboratory, achieving >8.5 Gb of data with mean read length 13 kb and N50 26 kb.