CMfinder—A Covariance Model Based RNA Motif Finding Algorithm: Appendix, additional technical details about the algorithm

نویسندگان

  • Zizhen Yao
  • Zasha Weinberg
  • Walter L. Ruzzo
چکیده

We used RNAfold in the Vienna package [1] to compute the minimal free energy for all subsequences in a given sequence. The ones whose length and number of stem-loops are within the range (default 30 ∼ 100 bases, 1 ∼ 2 stem loops), and are locally optimal (base paired at the ends, with no lower-energy states by extending or shrinking 2 bases at the ends) are selected. They are then sorted by the energy scaled by sequence length, and candidates are selected from the top of the list. We allow overlapped candidates as long as one of them is significantly longer than the other one.

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

CMfinder - a covariance model based RNA motif finding algorithm

MOTIVATION The recent discoveries of large numbers of non-coding RNAs and computational advances in genome-scale RNA search create a need for tools for automatic, high quality identification and characterization of conserved RNA motifs that can be readily used for database search. Previous tools fall short of this goal. RESULTS CMfinder is a new tool to predict RNA motifs in unaligned sequenc...

متن کامل

Online Appendix for: A Bounded Model of Time Variation in Trend Inflation, NAIRU and the Phillips Curve

This appendix contains two sections. The first is a technical appendix which describes the prior and MCMC algorithm used to estimate our bivariate model of inflation and unemployment (labelled Bi-UC in the paper). It also provides additional estimation details about the other models used for comparison. The second is section contains a prior predictive analysis. Papers cited in this appendix ar...

متن کامل

Mining frequent stem patterns from unaligned RNA sequences

MOTIVATION In detection of non-coding RNAs, it is often necessary to identify the secondary structure motifs from a set of putative RNA sequences. Most of the existing algorithms aim to provide the best motif or few good motifs, but biologists often need to inspect all the possible motifs thoroughly. RESULTS Our method RNAmine employs a graph theoretic representation of RNA sequences and dete...

متن کامل

Online Appendix for: Large Bayesian VARMAs

This appendix is divided into seven sections labelled A through G. Almost all details of the prior are specified in the paper itself, but the few remaining details about the prior are given in Appendix A. An outline of the MCMC algorithm was provided in the paper, but complete details and formulae are provided in Appendix B. Appendix C describes how we calculate the DIC which is one of the meth...

متن کامل

Online Appendix: Latent Factor Regressions for the Social Sciences

Appendix RoadMap In this appendix I provide additional details of materials omitted from the main paper. Appendix A includes a summary of technical contributions as well as details of the estimation algorithms. Appendices B-D provide additional insights into particular areas of the literature. Appendices E-F provide additional details on simulations and applications. A Variational Inference Alg...

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 2006