Biomedical subjects

John Rachlin

Publications and source records attributed to John Rachlin.

3 recordsLinked to original sources

PubMed2006

Biological context networks: a mosaic view of the interactome.

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.

Protein Interaction Mapping↗

PubMed2005

Computational tradeoffs in multiplex PCR assay design for SNP genotyping.

BACKGROUND: Multiplex PCR is a key technology for detecting infectious microorganisms, whole-genome sequencing, forensic analysis, and for enabling flexible yet low-cost genotyping. However, the design of a multiplex PCR assays requires the consideration of multiple competing objectives and physical constraints, and extensive computational analysis must be performed in order to identify the possible formation of primer-dimers that can negatively impact product yield. RESULTS: This paper examines the computational design limits of multiplex PCR in the context of SNP genotyping and examines tradeoffs associated with several key design factors including multiplexing level (the number of primer pairs per tube), coverage (the % of SNP whose associated primers are actually assigned to one of several available tube), and tube-size uniformity. We also examine how design performance depends on the total number of available SNPs from which to choose, and primer stringency criterial. We show that finding high-multiplexing/high-coverage designs is subject to a computational phase transition, becoming dramatically more difficult when the probability of primer pair interaction exceeds a critical threshold. The precise location of this critical transition point depends on the number of available SNPs and the level of multiplexing required. We also demonstrate how coverage performance is impacted by the number of available snps, primer selection criteria, and target multiplexing levels. CONCLUSION: The presence of a phase transition suggests limits to scaling Multiplex PCR performance for high-throughput genomics applications. Achieving broad SNP coverage rapidly transitions from being very easy to very hard as the target multiplexing level (# of primer pairs per tube) increases. The onset of a phase transition can be "delayed" by having a larger pool of SNPs, or loosening primer selection constraints so as to increase the number of candidate primer pairs per SNP, though the latter may produce other adverse effects. The resulting design performance tradeoffs define a benchmark that can serve as the basis for comparing competing multiplex PCR design optimization algorithms and can also provide general rules-of-thumb to experimentalists seeking to understand the performance limits of standard multiplex PCR.

Algorithms↗

PubMed2005

MuPlex: multi-objective multiplex PCR assay design.

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 http://genomics14.bu.edu:8080/MuPlex/MuPlex.html.

Algorithms↗