Multilevel Modeling and Inference of Transcription Regulation
نویسندگان
چکیده
The understanding of transcription regulation is a major goal of today's biology. The challenge is to utilize diverse high-throughput data in order to infer mechanistic models of transcription control. We propose a new model which integrates transcription factor-gene affinity, protein abundance, and gene expression profiles. The model provides a detailed, yet computationally tractable description of the relations between transcription factors, their binding sites at gene promoters, and the combinatorial regulation of transcription. At the core, our model manipulates dose-affinity-response functions that associate transcription factor concentrations and transcription factor-DNA affinities to determine the rate of transcription factor-DNA reactions. We study computational problems that arise in optimizing such models and develop polynomial algorithms for certain problems. We show how to assess missing values (notably protein abundance) and describe a novel framework to infer models from currently available data. On budding yeast carbohydrate metabolism data, our results demonstrate the sensitivity and specificity of the approach. They also suggest new active binding sites and a regulation model for the transcription program of the galactose system.
منابع مشابه
Multilevel (hierarchical) modeling: what it can and can’t do
Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in which regression coefficients are themselves given a model, whose parameters are also estimated from data. We illustrate the strengths and limitations of multilevel modeling through an example of the prediction of home radon levels in U.S. counties. The multilevel model is highly effective for pr...
متن کاملMultilevel (Hierarchical) Modeling: What It Can and Cannot Do
Multilevel (hierarchical) modeling is a generalization of linear and generalized linear modeling in which regression coefficients are themselves given a model, whose parameters are also estimated from data. We illustrate the strengths and limitations of multilevel modeling through an example of the prediction of home radon levels in U.S. counties. The multilevel model is highly effective for pr...
متن کاملTransformer-based Single-source Multilevel Inverter with Reduction in Number of Transformers
Single-source binary hybrid multilevel inverters with cascaded transformers have a bulky transformer connected to their main H-bridge cells in each phase. This bulky transformer has been eliminated in this work without any effect on operation and modulation strategies. The proposed topology has significant advantages from view point of dimensions and number of transformers, design of transforme...
متن کاملHeterogeneity in DNA multiple alignments: modeling, inference, and applications in motif finding.
Transcription factors bind sequence-specific sites in DNA to regulate gene transcription. Identifying transcription factor binding sites (TFBSs) is an important step for understanding gene regulation. Although sophisticated in modeling TFBSs and their combinatorial patterns, computational methods for TFBS detection and motif finding often make oversimplified homogeneous model assumptions for ba...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Journal of computational biology : a journal of computational molecular cell biology
دوره 11 2-3 شماره
صفحات -
تاریخ انتشار 2004