A neural network-based tool, TargetP, for large-scale subcellular location prediction of newly
identified proteins has been developed. Using N-terminal sequence information only, it …

Determining the subcellular localization of a protein is an important first step toward
understanding its function. Here, we describe the properties of three well-known N-terminal …

We present a neural network based method (ChloroP) for identifying chloroplast transit peptides
and their cleavage sites. Using cross‐validation, 88% of the sequences in our homology …

While sequencing of the human genome surprised us with how many protein-coding genes
there are, it did not fundamentally change our perspective on what a gene is. In contrast, the …

Characterization of the chloroplast proteome is needed to understand the essential
contribution of the chloroplast to plant growth and development. Here we present a large scale …

In bioinformatics, machine learning methods have been used to predict features embedded
in the sequences. In contrast to what is generally assumed, machine learning approaches …

Experimental proteome analysis was combined with a genome-wide prediction screen to
characterize the protein content of the thylakoid lumen of Arabidopsis chloroplasts. Soluble …

Recent progress in mapping transcription factor (TF) binding regions can largely be credited
to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for …

RNA sequencing has become widely used in gene expression profiling experiments. Prior
to any RNA sequencing experiment the quality of the RNA must be measured to assess …

The subcellular location of a protein is an important characteristic with functional implications,
and hence the problem of predicting subcellular localization from the amino acid …