In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
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Question: We describe a Multiplex Primer Prediction (MPP) algorithm to build multiplex compatible primer sets to amplify all members of large, diverse and unalignable sets of target sequences. The MPP algorithm is scalable to larger target sets than other available software, and it does not require a multiple sequence alignment. We applied it to questions in viral detection, and demonstrated that there are no universally conserved priming sequences among viruses and that it could require an unfeasibly large number of primers ($3700 18-mers or $2000 10-mers) to generate amplicons from all sequenced viruses. We then designed primer sets separately for each viral family, and for several diverse species such as foot-and-mouth disease virus (FMDV), hemagglutinin (HA) and neuraminidase (NA) segments of influenza A virus, Norwalk virus, and HIV-1. We empirically demonstrated the application of the software with a multiplex set of 16 short (10 nt) primers designed to amplify the Poxviridae family to produce a specific amplicon from vaccinia virus.

Answer: Multiplex primer prediction software for divergent targets

Question: Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets.

Answer: In silico pharmacology for drug discovery: applications to targets and beyond

Question: Rhubarb (Rheum emodi, family Polygonaceae) has been traditionally used as diuretic, liver stimulant, purgative/cathartic, stomachic, anticholesterolaemic, antitumour, antiseptic and tonic. A number of anthraquinone derivatives including emodin, aloe-emodin, physcion, chrysophanol, rhein, emodin glycoside and chrysophanol glycoside occur as the main chemical constituents. In the past few years, new components such as sulfemodin 8-O-b-D-glucoside, revandchinone-1, revandchinone-2, revandchinone-3, revandchinone-4, 6-methyl-rhein and 6-methyl aloe-emodin have been reported from the same species. Anthraquinone derivatives show evidence of antifungal, anti-microbial, anti-Parkinson's, anti-proliferative, immuno-enhancing, antiviral and antioxidant activities. This review covers published work on botany, chemistry and therapeutic uses of different components from rhubarb.

Answer:
Phytoconstituents and therapeutic uses of Rheum emodi wall. ex Meissn