Deep learning for plant genomics and crop improvement
Our era has witnessed tremendous advances in plant genomics, characterized by an
explosion of high-throughput techniques to identify multi-dimensional genome-wide …
explosion of high-throughput techniques to identify multi-dimensional genome-wide …
Machine learning: its challenges and opportunities in plant system biology
Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
Learning functional properties of proteins with language models
Data-centric approaches have been used to develop predictive methods for elucidating
uncharacterized properties of proteins; however, studies indicate that these methods should …
uncharacterized properties of proteins; however, studies indicate that these methods should …
Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure
Understanding the genetic regulatory code governing gene expression is an important
challenge in molecular biology. However, how individual coding and non-coding regions of …
challenge in molecular biology. However, how individual coding and non-coding regions of …
Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
The transcription regulatory network inside a eukaryotic cell is defined by the combinatorial
actions of transcription factors (TFs). However, TF binding studies in plants are too few in …
actions of transcription factors (TFs). However, TF binding studies in plants are too few in …
Dissecting cis-regulatory control of quantitative trait variation in a plant stem cell circuit
Cis-regulatory mutations underlie important crop domestication and improvement traits,.
However, limited allelic diversity has hindered functional dissection of the large number of …
However, limited allelic diversity has hindered functional dissection of the large number of …
Representation learning applications in biological sequence analysis
Although remarkable advances have been reported in high-throughput sequencing, the
ability to aptly analyze a substantial amount of rapidly generated biological …
ability to aptly analyze a substantial amount of rapidly generated biological …
When less is more: sketching with minimizers in genomics
The exponential increase in sequencing data calls for conceptual and computational
advances to extract useful biological insights. One such advance, minimizers, allows for …
advances to extract useful biological insights. One such advance, minimizers, allows for …
Limited conservation in cross-species comparison of GLK transcription factor binding suggested wide-spread cistrome divergence
Non-coding cis-regulatory variants in animal genomes are an important driving force in the
evolution of transcription regulation and phenotype diversity. However, cistrome dynamics in …
evolution of transcription regulation and phenotype diversity. However, cistrome dynamics in …
Peer: a comprehensive and multi-task benchmark for protein sequence understanding
We are now witnessing significant progress of deep learning methods in a variety of tasks
(or datasets) of proteins. However, there is a lack of a standard benchmark to evaluate the …
(or datasets) of proteins. However, there is a lack of a standard benchmark to evaluate the …