FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2019900412> ?p ?o ?g. }

• W2019900412 abstract "Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered. To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-κB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies. To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA. Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies. Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs." @default.
• W2019900412 created "2016-06-24" @default.
• W2019900412 creator A5008115246 @default.
• W2019900412 creator A5038764591 @default.
• W2019900412 creator A5045830123 @default.
• W2019900412 creator A5051248114 @default.
• W2019900412 creator A5053694878 @default.
• W2019900412 creator A5069556154 @default.
• W2019900412 creator A5075720865 @default.
• W2019900412 date "2007-12-01" @default.
• W2019900412 modified "2023-10-06" @default.
• W2019900412 title "Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions" @default.
• W2019900412 cites W1480252060 @default.
• W2019900412 cites W1498410508 @default.
• W2019900412 cites W1505084960 @default.
• W2019900412 cites W153767141 @default.
• W2019900412 cites W1577584933 @default.
• W2019900412 cites W1822814854 @default.
• W2019900412 cites W1961939221 @default.
• W2019900412 cites W1968453480 @default.
• W2019900412 cites W1974614108 @default.
• W2019900412 cites W1975297840 @default.
• W2019900412 cites W1980256638 @default.
• W2019900412 cites W1987122345 @default.
• W2019900412 cites W1999059147 @default.
• W2019900412 cites W2001208416 @default.
• W2019900412 cites W2007137661 @default.
• W2019900412 cites W2011189608 @default.
• W2019900412 cites W2013739996 @default.
• W2019900412 cites W2023825247 @default.
• W2019900412 cites W2042694610 @default.
• W2019900412 cites W2045519188 @default.
• W2019900412 cites W2056572892 @default.
• W2019900412 cites W2064879068 @default.
• W2019900412 cites W2068140368 @default.
• W2019900412 cites W2071063546 @default.
• W2019900412 cites W2071753700 @default.
• W2019900412 cites W2072852987 @default.
• W2019900412 cites W2076960251 @default.
• W2019900412 cites W2078844752 @default.
• W2019900412 cites W2079659879 @default.
• W2019900412 cites W2085442947 @default.
• W2019900412 cites W2085566684 @default.
• W2019900412 cites W2094036688 @default.
• W2019900412 cites W2095640709 @default.
• W2019900412 cites W2098823516 @default.
• W2019900412 cites W2100558818 @default.
• W2019900412 cites W2101025813 @default.
• W2019900412 cites W2108011868 @default.
• W2019900412 cites W2110863141 @default.
• W2019900412 cites W2114332734 @default.
• W2019900412 cites W2115979107 @default.
• W2019900412 cites W2116390865 @default.
• W2019900412 cites W2120746509 @default.
• W2019900412 cites W2121154174 @default.
• W2019900412 cites W2121298930 @default.
• W2019900412 cites W2122360987 @default.
• W2019900412 cites W2123243961 @default.
• W2019900412 cites W2124985974 @default.
• W2019900412 cites W2127284131 @default.
• W2019900412 cites W2127521865 @default.
• W2019900412 cites W2129185784 @default.
• W2019900412 cites W2130919037 @default.
• W2019900412 cites W2131000278 @default.
• W2019900412 cites W2134193442 @default.
• W2019900412 cites W2141936300 @default.
• W2019900412 cites W2143387112 @default.
• W2019900412 cites W2145992497 @default.
• W2019900412 cites W2146393977 @default.
• W2019900412 cites W2149096772 @default.
• W2019900412 cites W2149769193 @default.
• W2019900412 cites W2150557879 @default.
• W2019900412 cites W2151945801 @default.
• W2019900412 cites W2152741970 @default.
• W2019900412 cites W2154412571 @default.
• W2019900412 cites W2160626228 @default.
• W2019900412 cites W2166187656 @default.
• W2019900412 cites W2166277117 @default.
• W2019900412 cites W2166429927 @default.
• W2019900412 cites W2171220883 @default.
• W2019900412 cites W2288623603 @default.
• W2019900412 cites W2398197203 @default.
• W2019900412 cites W2409618034 @default.
• W2019900412 cites W2116215156 @default.
• W2019900412 cites W34631043 @default.
• W2019900412 doi "https://doi.org/10.1186/1471-2105-8-481" @default.
• W2019900412 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2265442" @default.
• W2019900412 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18093302" @default.
• W2019900412 hasPublicationYear "2007" @default.
• W2019900412 type Work @default.
• W2019900412 sameAs 2019900412 @default.
• W2019900412 citedByCount "36" @default.
• W2019900412 countsByYear W20199004122012 @default.
• W2019900412 countsByYear W20199004122013 @default.
• W2019900412 countsByYear W20199004122014 @default.
• W2019900412 countsByYear W20199004122015 @default.
• W2019900412 countsByYear W20199004122016 @default.
• W2019900412 countsByYear W20199004122017 @default.
• W2019900412 countsByYear W20199004122018 @default.
• W2019900412 countsByYear W20199004122019 @default.

• next