Inferring functional information from domain co-evolution

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Inferring functional information from domain co-evolution

MOTIVATION Co-evolution is a powerful mechanism for understanding protein function. Prior work in this area has shown that co-evolving proteins are more likely to share the same function than those that do not because of functional constraints. Many of the efforts founded on this observation, however, are at the level of entire sequences, implicitly assuming that the complete protein sequence f...

متن کامل

Inferring Network Structure from Co-Occurrences

We consider the problem of inferring the structure of a network from cooccurrence data: observations that indicate which nodes occur in a signaling pathway but do not directly reveal node order within the pathway. This problem is motivated by network inference problems arising in computational biology and communication systems, in which it is difficult or impossible to obtain precise time order...

متن کامل

Inferring protein-protein interaction networks from inter-protein sequence co-evolution

Interaction between proteins is a fundamental mechanism that underlies virtually all biological processes. Many important interactions are conserved across a large variety of species. The need to maintain interaction leads to a high degree of co-evolution between residues in the interface between partner proteins. The inference of proteinprotein interaction networks from the rapidly growing seq...

متن کامل

Inferring Functional Brain States Using Temporal Evolution of Regularized Classifiers

We present a framework for inferring functional brain state from electrophysiological (MEG or EEG) brain signals. Our approach is adapted to the needs of functional brain imaging rather than EEG-based brain-computer interface (BCI). This choice leads to a different set of requirements, in particular to the demand for more robust inference methods and more sophisticated model validation techniqu...

متن کامل

Inferring Approximate Functional Dependencies from Example Data

This paper proposes a kind of PAC (Probably Approximately Correct) learning framework for inferring a set of functional dependencies. A simple algorithm for inferring the set of approximate functional dependencies from a subset of a full tuple set (i.e. a set of all tuples in the relation) is presented. It is shown that the upper bound of the sample complexity, which is the number of example tu...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Bioinformatics

سال: 2005

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/bti723