Biclustering Gene Expressions Using Factor Graphs and the Max-Sum Algorithm

نویسندگان

  • Matteo Denitto
  • Alessandro Farinelli
  • Manuele Bicego
چکیده

Biclustering is an intrinsically challenging and highly complex problem, particularly studied in the biology field, where the goal is to simultaneously cluster genes and samples of an expression data matrix. In this paper we present a novel approach to gene expression biclustering by providing a binary Factor Graph formulation to such problem. In more detail, we reformulate biclustering as a sequential search for single biclusters and use an efficient optimization procedure based on the Max Sum algorithm. Such approach, drastically alleviates the scaling issues of previous approaches for biclustering based on Factor Graphs obtaining significantly more accurate results on synthetic datasets. A further analysis on two real-world datasets confirms the potentials of the proposed methodology when compared to alternative state of the art methods.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A biclustering approach based on factor graphs and the max-sum algorithm

Biclustering represents an intrinsically complex problem, where the aim is to perform a simultaneous rowand column-clustering of a given data matrix. Some recent approaches model this problem using factor graphs, so to exploit their ability to open the door to efficient optimization approaches for well designed function decompositions. However, while such models provide promising results, they ...

متن کامل

MAX-CSP, Graph Cuts and Statistical Physics

Baker’s technique, which was created over three decades ago, is a powerful tool for designing polynomial time approximation schemes (PTAS) for NP-hard optimization problems on planar graphs and their generalizations. In this paper, we propose a unified framework to formulate the optimization problems where the local constraints of these problems are encoded by functions attached on the vertices...

متن کامل

Mining a Sub-Matrix of Maximal Sum

Biclustering techniques have been widely used to identify homogeneous subgroups within large data matrices, such as subsets of genes similarly expressed across subsets of patients. Mining a max-sum sub-matrix is a related but distinct problem for which one looks for a (non-necessarily contiguous) rectangular sub-matrix with a maximal sum of its entries. Le Van et al. [6] already illustrated its...

متن کامل

Propagation-Based Biclustering Algorithm for Extracting Inclusion-Maximal Motifs

Biclustering, which is simultaneous clustering of columns and rows in data matrix, became an issue when classical clustering algorithms proved not to be good enough to detect similar expressions of genes under subset of conditions. Biclustering algorithms may be also applied to different datasets, such as medical, economical, social networks etc. In this article we explain the concept beneath h...

متن کامل

A Hybrid Continuous Max-Sum Algorithm for Decentralised Coordination

In this paper we tackle the problem of coordinating multiple decentralised agents with continuous state variables. Specifically we propose a hybrid approach, which combines the maxsum algorithm with continuous non-linear optimisation methods. We show that, for problems with acyclic factor graph representations, for suitable parameter choices and sufficiently fine state space discretisations, ou...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015