Computational technique for improvement of the position-weight matrices for the DNA/protein binding sites

نویسندگان

  • Naum I. Gershenzon
  • Gary D. Stormo
  • Ilya P. Ioshikhes
چکیده

Position-weight matrices (PWMs) are broadly used to locate transcription factor binding sites in DNA sequences. The majority of existing PWMs provide a low level of both sensitivity and specificity. We present a new computational algorithm, a modification of the Staden-Bucher approach, that improves the PWM. We applied the proposed technique on the PWM of the GC-box, binding site for Sp1. The comparison of old and new PWMs shows that the latter increase both sensitivity and specificity. The statistical parameters of GC-box distribution in promoter regions and in the human genome, as well as in each chromosome, are presented. The majority of commonly used PWMs are the 4-row mononucleotide matrices, although 16-row dinucleotide matrices are known to be more informative. The algorithm efficiently determines the 16-row matrices and preliminary results show that such matrices provide better results than 4-row matrices.

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

Computational approach for modeling and testing NF-kB binding sites

Motifs of Transcription Factor Binding Sites (TFBS) in DNA are commonly represented by the Position Weight Matrices (PWM). Recently Alamanova et al. devised a method for creating PWMs of transcription factors using 3D structure-based computation of protein-DNA free binding energies. We modify Alamanova et al. approach using volume-fraction corrected DFIREbased energy function (DDNA3) as a model...

متن کامل

Dinucleotide Weight Matrices for Predicting Transcription Factor Binding Sites: Generalizing the Position Weight Matrix

BACKGROUND Identifying transcription factor binding sites (TFBS) in silico is key in understanding gene regulation. TFBS are string patterns that exhibit some variability, commonly modelled as "position weight matrices" (PWMs). Though convenient, the PWM has significant limitations, in particular the assumed independence of positions within the binding motif; and predictions based on PWMs are u...

متن کامل

Study of PKA binding sites in cAMP-signaling pathway using structural protein-protein interaction networks

Backgroud: Protein-protein interaction, plays a key role in signal transduction in signaling pathways. Different approaches are used for prediction of these interactions including experimental and computational approaches. In conventional node-edge protein-protein interaction networks, we can only see which proteins interact but ‘structural networks’ show us how these proteins inter...

متن کامل

The Next Generation of Transcription Factor Binding Site Prediction

Finding where transcription factors (TFs) bind to the DNA is of key importance to decipher gene regulation at a transcriptional level. Classically, computational prediction of TF binding sites (TFBSs) is based on basic position weight matrices (PWMs) which quantitatively score binding motifs based on the observed nucleotide patterns in a set of TFBSs for the corresponding TF. Such models make t...

متن کامل

In silico investigation of lactoferrin protein characterizations for the prediction of anti-microbial properties

Lactoferrin (Lf) is an iron-binding multi-functional glycoprotein which has numerous physiological functions such as iron transportation, anti-microbial activity and immune response. In this study, different in silico approaches were exploited to investigate Lf protein properties in a number of mammalian species. Results showed that the iron-binding site, DNA and RNA-binding sites, signal pepti...

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:
  • Nucleic Acids Research

دوره 33  شماره 

صفحات  -

تاریخ انتشار 2005