Genomic information of Arabidopsis thaliana can be obtained from various public databases. Given that naming conventions often vary between databases and that the same genes can be annotated differently, we developed a web-based tool, KATANA (Kazusa Arabidopsis thaliana Annotation Abstract; http://www.kazusa.or.jp/katana/), to guide users searching for Arabidopsis genomic information to the rel...

Large volumes of genomic data have been generated for several plant species over the past decade, including structural sequence data and functional annotation at the genome level. Various technologies such as expressed sequence tags (ESTs), massively parallel signature sequencing (MPSS) and microarrays have been used to study gene expression and to provide functional data for many genes simulta...

Absorption, distribution, metabolism and excretion (ADME) studies represent a fundamental step in the early stages of drug discovery. In particular, absorption orally administered drugs, which occurs at intestinal level, has gained attention since poor oral bioavailability often led to failures for new approval. this context, several vitro preclinical models have been recently developed optimiz...

The age of omics is in full swing. Full genome sequences and the use of DNA microarrays to monitor gene expression on a genome-wide scale arrived on the scene a little over a dozen years ago, and today major developments in DNA sequencing technology have ushered in a new era in the study of gene regulation. Around the turn of the century, the introduction of massively parallel next-generation D...

One of the energies strongly needed by humans is electrical energy. Currently, Solar Power Plant (henceforth, PLTS) a source renewable energy and widely developed since PLTS environmentally friendly easy to obtain, specifically for countries are on equator such as Indonesia. with large capacity PT. Amman Mineral Nusa Tenggara (PT. AMNT) in collaboration Medcopower Sumbawa MPSS) Sinergi Era Ceme...

Abstract We present an algorithm for supervised learning using tensor networks, employing a step of data pre-processing by coarse-graining through sequence wavelet transformations. These transformations are represented as set network layers identical to those in multi-scale entanglement renormalization ansatz network. perform and regression tasks model based on matrix product states (MPSs) acti...