A framework for evaluating epidemic forecasts.

Background: Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative methods vs.

Metabolic and Transcriptional Reprogramming in Developing Soybean (Glycine max) Embryos.

Soybean (Glycine max) seeds are an important source of seed storage compounds, including protein, oil, and sugar used for food, feed, chemical, and biofuel production. We assessed detailed temporal transcriptional and metabolic changes in developing soybean embryos to gain a systems biology view of developmental and metabolic changes and to identify potential targets for metabolic engineering. Two major developmental and metabolic transitions were captured enabling identification of potential metabolic engineering targets specific to seed filling and to desiccation.

An enhanced beam search algorithm for the Shortest Common Supersequence Problem.

The Shortest Common Supersequence Problem asks to obtain a shortest string that is a supersequence of every member of a given set of strings. It has applications, among others, in data compression and oligonucleotide microarray production. The problem is NP-hard, and the existing exact solutions are impractical for large instances.

A hyper-heuristic for the Longest Common Subsequence problem.

The Longest Common Subsequence Problem is the problem of finding a longest string that is a subsequence of every member of a given set of strings. It has applications in FPGA circuit minimization, data compression, and bioinformatics, among others. The problem is NP-hard in its general form, which implies that no exact polynomial-time algorithm currently exists for the problem.