Predicting a set of minimal free energy RNA secondary structures common to two sequences.
about
The multipartite mitochondrial genome of Liposcelis bostrychophila: insights into the evolution of mitochondrial genomes in bilateral animalsSimulFold: simultaneously inferring RNA structures including pseudoknots, alignments, and trees using a Bayesian MCMC frameworkA benchmark of multiple sequence alignment programs upon structural RNAs.Multilign: an algorithm to predict secondary structures conserved in multiple RNA sequencesR-Coffee: a method for multiple alignment of non-coding RNAEfficient pairwise RNA structure prediction and alignment using sequence alignment constraintsAn enhanced RNA alignment benchmark for sequence alignment programsAccurate multiple sequence-structure alignment of RNA sequences using combinatorial optimizationSemiautomated improvement of RNA alignmentsEfficient pairwise RNA structure prediction using probabilistic alignment constraints in DynalignStructure Prediction: New Insights into Decrypting Long Noncoding RNAsSearching for IRESIntegrating chemical footprinting data into RNA secondary structure predictionRNA secondary structure analysis using RNAstructurePareto optimization in algebraic dynamic programmingThe peculiarities of large intron splicing in animals.Complete mitochondrial genomes of Taenia multiceps, T. hydatigena and T. pisiformis: additional molecular markers for a tapeworm genus of human and animal health significanceDetection of non-coding RNAs on the basis of predicted secondary structure formation free energy change.Can Clustal-style progressive pairwise alignment of multiple sequences be used in RNA secondary structure prediction?Genomic mid-range inhomogeneity correlates with an abundance of RNA secondary structuresTRANSAT-- method for detecting the conserved helices of functional RNA structures, including transient, pseudo-knotted and alternative structuresNon-coding RNA detection methods combined to improve usability, reproducibility and precision.PicXAA-R: efficient structural alignment of multiple RNA sequences using a greedy approach.Using the RNAstructure Software Package to Predict Conserved RNA StructuresMolecular characterization of a novel Ljungan virus (Parechovirus; Picornaviridae) reveals a fourth genotype and indicates ancestral recombination.An alignment-free approach for eukaryotic ITS2 annotation and phylogenetic inference.Dynalign II: common secondary structure prediction for RNA homologs with domain insertionsFast online and index-based algorithms for approximate search of RNA sequence-structure patterns.Identifying and searching for conserved RNA localisation signals.Energy parameters and novel algorithms for an extended nearest neighbor energy model of RNAA set of nearest neighbor parameters for predicting the enthalpy change of RNA secondary structure formationDevelopment of lead hammerhead ribozyme candidates against human rod opsin mRNA for retinal degeneration therapy.RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.Improving the prediction of RNA secondary structure by detecting and assessing conserved stems.Cassandra retrotransposons carry independently transcribed 5S RNARNA localization signals: deciphering the message with bioinformatics.A bioinformatics search pipeline, RNA2DSearch, identifies RNA localization elements in Drosophila retrotransposons.Detecting and comparing non-coding RNAs in the high-throughput eraAntisense Oligonucleotides Targeting Influenza A Segment 8 Genomic RNA Inhibit Viral Replication.On the importance of cotranscriptional RNA structure formation
P2860
Q21089887-D5763E93-0153-4675-8CA8-208FF395D1DBQ21563523-D0EEA074-6F2A-4B4C-9B91-77C3955D10C0Q24523666-43E55603-D351-45C1-A0DE-11C4A6872BE0Q24618202-78A71682-03EC-4E5A-941E-7AE029D94AFAQ24649838-9723E9C4-BC0C-4F91-97C5-80B7E13C31A1Q24669554-4E9DFD6E-13D5-4816-8168-8216B3D6C193Q24673495-D7F594DB-8AEA-4A6B-AB72-6556405A06A0Q24673731-5B4BF556-5641-4827-9AB4-66B9C2911BF1Q24676170-126F10C0-9A40-4615-A410-ACBE95B56512Q24684612-C213E791-8AE8-406C-B4A4-AE7DA69A274EQ26775139-46968516-7A36-4411-9E70-612CE5FCDF4DQ27477494-ACCF198A-8525-434D-AA3E-72CE6CAE21BCQ28484429-0CAF4143-9550-4345-9DE5-81FBE2FB5EADQ28655982-346AEBEA-AD73-4148-8BD6-7217C826D9F1Q30656763-5D5C8C64-BEDB-4231-94C1-C5A40A18DF96Q30894453-1DCD2BFD-EB73-4D31-9854-97339FD0C9E1Q30986280-83DA956F-CFA7-4B72-869E-A99863E59115Q33237759-55AAFF08-EAB5-478E-BFCD-F687FB0A9A2EQ33287230-0A262CF7-E7A9-49FC-9506-6EAD6C6DFD13Q33343297-6A5FD29C-4D8B-42AF-A8ED-7B8FA27D05D8Q33621382-E44BB053-CFD8-4D3F-B116-542F724318C8Q33709924-BC200257-063D-4ACD-92E3-D8508668A440Q33827018-6FCD8979-DB8D-4971-B35F-DA039EFF44B1Q33863245-240948C4-85E0-4858-86A7-80F0FD0DDDF2Q33928915-84E68CF3-C6CD-4942-B2AD-B1944EEAEB00Q34064568-BBEA33E2-9342-4FA8-ADE4-FCF6CCDFF3F6Q34711944-7C6BB207-BA1D-4DC8-AACA-FCA0AFF187DDQ34832981-34447CD2-B05B-45F2-8333-2D6D1CDB6197Q34857080-EB79B009-3CC8-44DF-BC14-DE8D34DCB62DQ35105853-848C6238-706B-4DFA-B0E6-D87828DDD4A3Q35127973-AC24C43D-3C18-4E67-ADC3-2DDA6A17A556Q36073816-EDCA282D-1FD9-4B03-81BF-C3A132580457Q36256366-802E1419-9A9F-4808-9D23-884C197AB3A3Q36457228-80437F4E-0546-441B-91FC-07302A3B160EQ36557913-4A7064E7-A53D-4A4D-85FB-FBC55CA2146CQ36798894-43AC3292-EC1F-4B3E-83E2-E6AC563EA88EQ37111421-DD53D9B9-FDEE-4C82-AA06-5646D4B6E178Q37139041-8DBDDB11-8E06-4E67-B170-61D52916526DQ37346000-8E59E537-DB38-4931-991A-E6F9F34761CFQ38153167-7E394DF5-164C-49E7-BB79-BCE8B2B891C2
P2860
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
description
2005 nî lūn-bûn
@nan
2005 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
name
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@ast
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@en
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@nl
type
label
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@ast
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@en
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@nl
prefLabel
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@ast
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@en
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@nl
P356
P1433
P1476
Predicting a set of minimal free energy RNA secondary structures common to two sequences.
@en
P2093
David H Mathews
P304
P356
10.1093/BIOINFORMATICS/BTI349
P407
P577
2005-02-24T00:00:00Z