We value the option of subcontracting to improve Þnancial performance and system coordination by analyzing a competitive stochastic investment game with recourse. The manufacturer and subcontractor decide separately on their capacity investment levels. Then demand uncertainty is resolved and both parties have the option to subcontract when deciding on their production and sales. We analyze and present outsourcing conditions for three contract types:(1) price-only contracts where an ex-ante transfer price is set for each unit supplied by the subcontractor; (2) incomplete contracts, where both parties negotiate over the subcontracting transfer; and (3) state-dependent price-only and incomplete contracts for which we show an equivalence result.While subcontracting with these three contract types can coordinate production decisions in the supply system, only state-dependent contracts can eliminate all decentralization costs and coordinate capacity investment decisions. The minimally sufficient price-only contract that coordinates our supply chain speciÞes transfer prices for a small number (6 in our model) of contingent scenarios. Our game-theoretic model allows the analysis of the role of transfer prices and of the bargaining power of buyer and supplier. We Þnd that sometimes Þrms may be better off leaving some contract parameters unspeciÞed ex-ante and agreeing to negotiate ex-post. Also, a price-focused strategy for managing subcontractors can backÞre because a lower transfer price may decrease the manufacturer's proÞt. Finally, as with Þnancial options, the option value of subcontracting increases as markets are more volatile or more negatively correlated.

We have developed a web-enabled system called MuPlex that aids researchers in the design of multiplex PCR assays. Multiplex PCR is a key technology for an endless list of applications, including detecting infectious microorganisms, whole-genome sequencing and closure, forensic analysis and for enabling flexible yet low-cost genotyping. However, the design of a multiplex PCR assays is computationally challenging because it involves tradeoffs among competing objectives, and extensive computational analysis is required in order to screen out primer-pair cross interactions. With MuPlex, users specify a set of DNA sequences along with primer selection criteria, interaction parameters and the target multiplexing level. MuPlex designs a set of multiplex PCR assays designed to cover as many of the input sequences as possible. MuPlex provides multiple solution alternatives that reveal tradeoffs among competing objectives. MuPlex is uniquely designed for large-scale multiplex PCR assay design in an automated high-throughput environment, where high coverage of potentially thousands of single nucleotide polymorphisms is required. The server is available at .

Experimental data exists for only a vanishingly small fraction of sequenced microbial genes. This community page discusses the progress made by the COMBREX project to address this important issue using both computational and experimental resources.

Network models are a fundamental tool for the visualization and analysis of molecular interactions occurring in biological systems. While broadly illuminating the molecular machinery of the cell, graphical representations of protein interaction networks mask complex patterns of interaction that depend on temporal, spatial, or condition-specific contexts. In this paper, we introduce a novel graph construct called a biological context network that explicitly captures these changing patterns of interaction from one biological context to another. We consider known gene ontology biological process and cellular component annotations as a proxy for context, and show that aggregating small process-specific protein interaction sub-networks leads to the emergence of observed scale-free properties. The biological context model also provides the basis for characterizing proteins in terms of several context-specific measures, including 'interactive promiscuity,' which identifies proteins whose interacting partners vary from one context to another. We show that such context-sensitive measures are significantly better predictors of knockout lethality than node degree, reaching better than 70% accuracy among the top scoring proteins.

The COMBREX database (COMBREX-DB; combrex.bu.edu) is an online repository of information related to (i) experimentally determined protein function, (ii) predicted protein function, (iii) relationships among proteins of unknown function and various types of experimental data, including molecular function, protein structure, and associated phenotypes. The database was created as part of the novel COMBREX (COMputational BRidges to EXperiments) effort aimed at accelerating the rate of gene function validation. It currently holds information on ∼3.3 million known and predicted proteins from over 1000 completely sequenced bacterial and archaeal genomes. The database also contains a prototype recommendation system for helping users identify those proteins whose experimental determination of function would be most informative for predicting function for other proteins within protein families. The emphasis on documenting experimental evidence for function predictions, and the prioritization of uncharacterized proteins for experimental testing distinguish COMBREX from other publicly available microbial genomics resources. This article describes updates to COMBREX-DB since an initial description in the 2011 NAR Database Issue.