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Published online 19 March 2004
Nucleic Acids Research, 2004, Vol. 32, No. 5 1792-1797
Oxford University Press
MUSCLE: multiple sequence alignment with high accuracy and high throughput
195 Roque Moraes Drive, Mill Valley, CA 94941, USA
*Email: bob{at}drive5.com
Received January 19, 2004; Revised January 30, 2004; Accepted February 24, 2004
| ABSTRACT |
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We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
| INTRODUCTION |
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Multiple alignments of protein sequences are important in many applications, including phylogenetic tree estimation, structure prediction and critical residue identification. The most natural formulation of the computational problem is to define a model of sequence evolution that assigns probabilities to elementary sequence edits and seeks a most probable directed graph in which edges represent edits and terminal nodes are the observed sequences. No tractable method for finding such a graph is known. A heuristic alternative is to seek a multiple alignment that optimizes the sum of pairs (SP) score, i.e. the sum of pairwise alignment scores. Optimizing the SP score is NP complete (1) and can be achieved by dynamic programming with time and space complexity O(LN) in the sequence length L and number of sequences N (2). A more popular strategy is the progressive method (3,4), which first estimates a tree and then constructs a pairwise alignment of the subtrees found at each internal node. A subtree is represented by its profile, a multiple alignment treated as a sequence by regarding each column as an alignable symbol. A variant on this strategy is used by T-Coffee (5), which aligns profiles by optimizing a score derived from local and global alignments of all pairs of input sequences. Misalignments by progressive methods are sometimes readily apparent (Fig. 1), motivating further processing (refinement). For a recent review of multiple alignment methods, see Notredame (6). Here we describe MUSCLE (multiple sequence comparison by log-expectation), a new computer program for multiple protein sequence alignment.
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| MUSCLE algorithm |
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Here we give an overview of the algorithm; a more detailed discussion is given in Edgar (submitted). Following guide tree construction, the fundamental step is pairwise profile alignment, which is used first for progressive alignment and then for refinement. This is similar to the strategies used by PRRP (7) and MAFFT (8).
Distance measures and guide tree estimation
MUSCLE uses two distance measures for a pair of sequences: a kmer distance (for an unaligned pair) and the Kimura distance (for an aligned pair). A kmer is a contiguous subsequence of length k, also known as a word or k-tuple. Related sequences tend to have more kmers in common than expected by chance. The kmer distance is derived from the fraction of kmers in common in a compressed alphabet, which we have previously shown to correlate well with fractional identity (9). This measure does not require an alignment, giving a significant speed advantage. Given an aligned pair of sequences, we compute the pairwise identity and convert to an additive distance estimate, applying the Kimura correction for multiple substitutions at a single site (10). Distance matrices are clustered using UPGMA (11), which we find to give slightly improved results over neighbor-joining (12), despite the expectation that neighbor-joining will give a more reliable estimate of the evolutionary tree. This can be explained by assuming that in progressive alignment, the best accuracy is obtained at each node by aligning the two profiles that have fewest differences, even if they are not evolutionary neighbors.
Profile alignment
In order to apply pairwise alignment to profiles, a scoring function must be defined on an aligned pair of profile positions, i.e. a pair of multiple alignment columns [see, for example Edgar and Sjolander (13)]. Let i and j be amino acid types, pi the background probability of i, pij the joint probability of i and j being aligned to each other, fxi the observed frequency of i in column x of the first profile, and f xG the observed frequency of gaps in that column at position x in the family (similarly for position y in the second profile). The estimated probability
xi of observing amino acid i in position x can be derived from fx, typically by adding heuristic pseudo-counts or by using Bayesian methods such as Dirichlet mixture priors (14). MUSCLE uses a new profile function we call the log-expectation (LE) score:
LExy = (1 f xG) (1 f yG) log
i
j f xi f yj pij/pi pj1
This is a modified version of the log-average function (15):
LAxy = log
i
j
xi
yj pij/pi pj2
MUSCLE uses probabilities pi and pij derived from the 240 PAM VTML matrix (16). Frequencies fi are normalized to sum to 1 when indels are present (otherwise the logarithm becomes increasingly negative with increasing numbers of gaps even when aligning conserved or similar residues). The factor (1 fG) is the occupancy of a column, introduced to encourage more highly occupied columns to align. Position-specific gap penalties are used, employing heuristics similar to those found in MAFFT and LAGAN (17).
Algorithm
The high-level flow is depicted in Figure 2.
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Stage 1, Draft progressive. The goal of the first stage is to produce a multiple alignment, emphasizing speed over accuracy.
1.1 The kmer distance is computed for each pair of input sequences, giving distance matrix D1.
1.2 Matrix D1 is clustered by UPGMA, producing binary tree TREE1.
1.3 A progressive alignment is constructed by following the branching order of TREE1. At each leaf, a profile is constructed from an input sequence. Nodes in the tree are visited in prefix order (children before their parent). At each internal node, a pairwise alignment is constructed of the two child profiles, giving a new profile which is assigned to that node. This produces a multiple alignment of all input sequences, MSA1, at the root.
Stage 2, Improved progressive. The main source of error in the draft progressive stage is the approximate kmer distance measure, which results in a suboptimal tree. MUSCLE therefore re-estimates the tree using the Kimura distance, which is more accurate but requires an alignment.
2.1 The Kimura distance for each pair of input sequences is computed from MSA1, giving distance matrix D2.
2.2 Matrix D2 is clustered by UPGMA, producing binary tree TREE2.
2.3 A progressive alignment is produced following TREE2 (similar to 1.3), producing multiple alignment MSA2. This is optimized by computing alignments only for subtrees whose branching orders changed relative to TREE1.
Stage 3, Refinement.
3.1 An edge is chosen from TREE2 (edges are visited in order of decreasing distance from the root).
3.2 TREE2 is divided into two subtrees by deleting the edge. The profile of the multiple alignment in each subtree is computed.
3.3 A new multiple alignment is produced by re-aligning the two profiles.
3.4 If the SP score is improved, the new alignment is kept, otherwise it is discarded.
Steps 3.13.4 are repeated until convergence or until a user-defined limit is reached. This is a variant of tree-dependent restricted partitioning (18).
Complete multiple alignments are available at steps 1.3, 2.3 and 3.4, at which points the algorithm may be terminated. We refer to the first two stages alone as MUSCLE-p, which produces MSA2. MUSCLE-p has time complexity O(N2L + NL2) and space complexity O(N2 + NL + L2). Refinement adds an O(N3L) term to the time complexity.
| Assessment |
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We assessed the performance of MUSCLE on four sets of reference alignments: BAliBASE (19,20), SABmark (21), SMART (2224) and a new benchmark, PREFAB. We compared these with four other methods: CLUSTALW (25), probably the most widely used program at the time of writing; T-Coffee, which has the best BAliBASE score reported to date; and two MAFFT scripts: FFTNS1, the fastest previously published method known to the author (in which diagonal finding by fast Fourier transform is enabled and a progressive alignment constructed), and NWNSI, the slowest but most accurate of the MAFFT methods (in which fast Fourier transform is disabled and refinement is enabled). Tested versions were MUSCLE 3.2, CLUSTALW 1.82, T-Coffee 1.37 and MAFFT 3.82. We also evaluated MUSCLE-p, in which the refinement stage is omitted. We also tried Align-m 1.0 (21), but found in many cases that the program either aborted or was impractically slow on the larger alignments found in SMART and PREFAB.
BAliBASE. We used version 2 of the BAliBASE benchmark, reference sets Ref 1Ref 5. Other reference sets contain repeats, inversions and transmembrane helices, for which none of the tested algorithms is designed.
SABmark. We used version 1.63 of the SABmark reference alignments, which consists of two subsets: Superfamily and Twilight. All sequences have known structure. The Twilight set contains 1994 domains from the Astral database (26) with pairwise sequence similarity e-values
1, divided into 236 folds according to the SCOP classification (27). The Superfamily set contains sequences of pairwise identity
50%, divided into 462 SCOP superfamilies. Each pair of structures was aligned with two structural aligners: SOFI (28) and CE (29), producing a sequence alignment from the consensus in which only high-confidence regions are retained. Input sets range from three to 25 sequences, with an average of eight and an average sequence length of 179.
SMART. SMART contains multiple alignments refined by experts, focusing primarily on signaling domains. While structures were considered where known, sequence methods were also used to aid construction of the database, so SMART is not suitable as a definitive benchmark. However, conventional wisdom [e.g. Fischer et al. (30)] holds that machine-assisted experts can produce superior alignments to automated methods, so performance on this set is of interest for comparison. We used a version of SMART downloaded in July 2000, before the first version of MUSCLE was made available; eliminating the possibility that MUSCLE was used to aid construction. We discarded alignments of more than 100 sequences in order to make the test tractable for T-Coffee, leaving 267 alignments averaging 31 sequences of length 175.
PREFAB. The methods used to create databases such as BAliBASE and SMART are time-consuming and demand significant expertise, making a fully automated protocol desirable. Perhaps the most obvious approach is to generate sequence alignments from automated alignments of multiple structures, but this is fraught with difficulties; see for example Eidhammer et al. (31). With this in mind, we constructed a new test set, PREFAB (protein reference alignment benchmark) which exploits methodology (21,32,33), test data (13,34,35) and statistical methods (19) that have previously been applied to alignment accuracy assessment. The protocol is as follows. Two proteins are aligned by a structural method that does not incorporate sequence similarity. Each sequence is used to query a database, from which high-scoring hits are collected. The queries and their hits are combined and aligned by a multiple sequence method. Accuracy is assessed on the original pair alone, by comparison with their structural alignment. Three test sets selected from the FSSP database (36) were used as described in Sadreyev and Grishin (34) (data kindly provided by Ruslan Sadreyev), and Edgar and Sjolander (13,35), which we call SG, PP1 and PP2, respectively. These three sets vary mainly in their selection criteria. PP1 and PP2 contain pairs with sequence identity
30%. PP1 was designed to select pairs that have high structural similarity, requiring a z-score of
15 and a root mean square deviation (r.m.s.d.) of
2.5 Å. PP2 selected more diverged pairs with a z-score of
8 and
12, and an r.m.s.d. of
3.5 Å. SG contains pairs sampled from three ranges of sequence identity: 015, 1530 and 3097%, with no z-score or r.m.s.d. limits. We re-aligned each pair of structures using the CE aligner (29), and retained only those pairs for which FSSP and CE agreed on 50 or more positions. This was designed to minimize questionable and ambiguous structural alignments as done in SABmark and MaxBench (33). We used the full-chain sequence of each structure to make a PSI-BLAST (37,38) search of the NCBI non-redundant protein sequence database (39), keeping locally aligned regions of hits with e-values below 0.01. Hits were filtered to 80% maximum identity (including the query), and 24 selected at random. Finally, each pair of structures and their remaining hits were combined to make sets of
50 sequences. The limit of 50 was arbitrarily chosen to make the test tractable on a desktop computer for some of the more resource-intensive methods, in particular T-Coffee (which needed 10 CPU days, as noted in Table 4). The final set, PREFAB version 3.0, has 1932 alignments averaging 49 sequences of length 240, of which 178 positions in the structure pair are found in the consensus of FSSP and CE.
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Accuracy measurement
We used three accuracy measures: Q, TC and APDB. Q (quality) is the number of correctly aligned residue pairs divided by the number of residue pairs in the reference alignment. This has previously been termed the developer score (32) and SPS (40). TC (total column score) is the number of correctly aligned columns divided by the number of columns in the reference alignment; this is Thompson et al.s CS and is equivalent to Q in the case of two sequences (as in PREFAB). APDB (41) is derived from structures alone; no reference alignment of the sequences or structures is needed. For BAliBASE, we use Q and TC, measured only on core blocks as annotated in the database. For PREFAB, we use Q, including only those positions on which CE and FSSP agree, and also APDB. For SMART, we use Q and TC computed for all columns. For SABmark, we average the Q score over each pair of sequences. TC score is not applicable to SABmark as the reference alignments are pairwise.
Statistical analysis
Following Thompson et al. (19), statistical significance is measured by a Friedman rank test (42), which is more conservative than the Wilcoxon test that has also been used for alignment accuracy discrimination (5,7,8) as fewer assumptions are made about the population distribution. In particular, the Wilcoxon test assumes a symmetrical difference between two methods, but in practice we sometimes observe a significant skew. PREFAB and SABmark use automated structure alignment methods, which sometimes produce questionable results. Many low-quality regions are eliminated by taking the consensus between two independent aligners, but some may remain. In PREFAB, assessment of a multiple alignment is made on a single pair of sequences, which may be more or less accurately aligned than the average over all pairs. In SABmark, the upper bound on Q is less than 1 to a varying degree because the pairwise reference alignments may not be mutually consistent. These effects can be viewed as introducing noise into the experiment, and a single accuracy measurement may be subject to error. However, as the structural aligners do not use primary sequence, these errors are unbiased with respect to sequence methods. A difference in accuracy between two sequence alignment methods can therefore be established by the Friedman test, and the measured difference in average accuracy will be approximately correct when measured over a sufficient number of samples.
| RESULTS |
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Quality scores and CPU times are summarized in Tables 1234567; rankings and statistical significance on PREFAB and BAliBASE for all pairs of methods are given in Table 8. On all test sets and quality measures, MUSCLE achieves the highest ranking (in some cases jointly with other methods due to lack of statistical significance), and MUSCLE-p is statistically indistinguishable from T-Coffee and NWNSI. MUSCLE achieves the highest BAliBASE score reported to date, but the improvement of 1.6% in Q and 2.2% in TC over T-Coffee has low significance (P = 0.15). A similar result is found on SABmark, where MUSCLE achieves a 1.5% improvement over T-Coffee in Q with P = 0.14. The Q score on PREFAB is best able to distinguish between methods, giving statistically significant rankings to MUSCLE > MUSCLE-p, MUSCLE > T-Coffee, MUSCLE > NWNSI and MUSCLE-p > NWNSI. SMART also ranks MUSCLE highest. SMART cannot be considered definitive due to the use of sequence methods in construction of the database, although any bias from this source is likely to favor methods that were available to the SMART developers (i.e. to be against MUSCLE). The SMART results could be interpreted as suggesting that MUSCLE alignments are more consistent with refinements made by human experts. The APDB score appears to be relatively insensitive, showing no significant improvement due to the refinement stage of MUSCLE (similarly for MAFFT; not shown), and is not able to distinguish between the four highest scoring methods. We speculate that the scatter observed in the correlation between APDB and more conventional measures such as TC (40) injects sufficient noise to obscure meaningful differences in accuracy that can be resolved using Q. The low rank of Align-m on SABmark differs from results quoted by Van Walle et al. (21), who assessed pairwise alignments produced by an intermediate step in the algorithm, whereas we used the final multiple alignment.
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Resource requirements for large numbers of sequences
To investigate resource requirements for increasing number of sequences N, we used the Rose sequence generator (43) (complete results not shown). In agreement with other studies, [e.g. Katoh et al. (8)], we found that T-Coffee was unable to align more than approximately 102 sequences of typical length on a current desktop computer. CLUSTALW was able to align a few hundred sequences, with a practical limit around N = 103 where CPU time begins to scale approximately as N4. The largest set had 5000 sequences of average length 350. MUSCLE-p completed this test in 7 min, compared with 10 min for FFTNS1; we estimate that CLUSTALW would need approximately 1 year.
| DISCUSSION |
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We have described a new multiple sequence alignment algorithm, MUSCLE, and presented evidence that it creates alignments with average accuracy comparable with or superior to the best current methods. It should be emphasized that performance differences between the better methods emerge only when averaged over a large number of test cases, even when alignments are considered trustworthy. For example, on BAliBASE, the lowest scoring of the tested methods (FFTNS1) achieved a higher Q than the highest scoring (MUSCLE) in 21 out of 141 alignments and tied in 19 more; compared with T-Coffee, MUSCLE scored higher or tied in 95 cases, but lower in 24. This suggests the use of multiple algorithms and careful inspection of the results. MUSCLE is comparable in speed with CLUSTALW, completing a test set (PREFAB) averaging 49 sequences of length 240 in about half the time. The progressive method MUSCLE-p, which has average accuracy statistically indistinguishable from T-Coffee and the most accurate MAFFT script, is the fastest algorithm known to the author for large numbers of sequences, able to align 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE software, source code and test data are freely available at: http://www.drive5. com/muscle.
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Y. Bulliard, P. Turelli, U. F. Rohrig, V. Zoete, B. Mangeat, O. Michielin, and D. Trono Functional Analysis and Structural Modeling of Human APOBEC3G Reveal the Role of Evolutionarily Conserved Elements in the Inhibition of Human Immunodeficiency Virus Type 1 Infection and Alu Transposition J. Virol., December 1, 2009; 83(23): 12611 - 12621. [Abstract] [Full Text] [PDF] |
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C. Blouin, S. Perry, A. Lavell, E. Susko, and A. J. Roger Reproducing the manual annotation of multiple sequence alignments using a SVM classifier Bioinformatics, December 1, 2009; 25(23): 3093 - 3098. [Abstract] [Full Text] [PDF] |
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P. Deschamps and D. Moreira Signal Conflicts in the Phylogeny of the Primary Photosynthetic Eukaryotes Mol. Biol. Evol., December 1, 2009; 26(12): 2745 - 2753. [Abstract] [Full Text] [PDF] |
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M. Ortiz, N. Guex, E. Patin, O. Martin, I. Xenarios, A. Ciuffi, L. Quintana-Murci, and A. Telenti Evolutionary Trajectories of Primate Genes Involved in HIV Pathogenesis Mol. Biol. Evol., December 1, 2009; 26(12): 2865 - 2875. [Abstract] [Full Text] [PDF] |
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M. Marz, A. Donath, N. Verstraete, V. T. Nguyen, P. F. Stadler, and O. Bensaude Evolution of 7SK RNA and Its Protein Partners in Metazoa Mol. Biol. Evol., December 1, 2009; 26(12): 2821 - 2830. [Abstract] [Full Text] [PDF] |
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K. Mukherjee, L. Brocchieri, and T. R. Burglin A Comprehensive Classification and Evolutionary Analysis of Plant Homeobox Genes Mol. Biol. Evol., December 1, 2009; 26(12): 2775 - 2794. [Abstract] [Full Text] [PDF] |
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B. Bentlage, P. Cartwright, A. A. Yanagihara, C. Lewis, G. S. Richards, and A. G. Collins Evolution of box jellyfish (Cnidaria: Cubozoa), a group of highly toxic invertebrates Proc R Soc B, November 25, 2009; (2009) rspb.2009.1707v2. [Abstract] [Full Text] [PDF] |
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C.-H. Chen, T.-J. Chuang, B.-Y. Liao, and F.-C. Chen Scanning for the Signatures of Positive Selection for Human-Specific Insertions and Deletions Gen Biol Evol, November 23, 2009; 2009(0): 415 - 419. [Abstract] [Full Text] [PDF] |
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R. C. Thomson and H. B. Shaffer Sparse Supermatrices for Phylogenetic Inference: Taxonomy, Alignment, Rogue Taxa, and the Phylogeny of Living Turtles Syst Biol, November 11, 2009; (2009) syp075v1. [Abstract] [Full Text] [PDF] |
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J. Muller, D. Szklarczyk, P. Julien, I. Letunic, A. Roth, M. Kuhn, S. Powell, C. von Mering, T. Doerks, L. J. Jensen, et al. eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations Nucleic Acids Res., November 9, 2009; (2009) gkp951v1. [Abstract] [Full Text] [PDF] |
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A. R. Jex, R. S. Hall, D. T. J. Littlewood, and R. B. Gasser An integrated pipeline for next-generation sequencing and annotation of mitochondrial genomes Nucleic Acids Res., November 5, 2009; (2009) gkp883v1. [Abstract] [Full Text] [PDF] |
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M. S. Barker, H. Vogel, and M. E. Schranz Paleopolyploidy in the Brassicales: Analyses of the Cleome Transcriptome Elucidate the History of Genome Duplications in Arabidopsis and Other Brassicales Gen Biol Evol, November 3, 2009; 2009(0): 391 - 399. [Abstract] [Full Text] [PDF] |
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W. J. Kress, D. L. Erickson, F. A. Jones, N. G. Swenson, R. Perez, O. Sanjur, and E. Bermingham Plant DNA barcodes and a community phylogeny of a tropical forest dynamics plot in Panama PNAS, November 3, 2009; 106(44): 18621 - 18626. [Abstract] [Full Text] [PDF] |
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W. C. Wilson, B. J. Hindson, E. S. O'Hearn, S. Hall, C. Tellgren-Roth, C. Torres, P. Naraghi-Arani, J. O. Mecham, and R. J. Lenhoff A multiplex real-time reverse transcription polymerase chain reaction assay for detection and differentiation of Bluetongue virus and Epizootic hemorrhagic disease virus serogroups J Vet Diagn Invest, November 1, 2009; 21(6): 760 - 770. [Abstract] [Full Text] [PDF] |
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M. D. Wilkerson, Y. Ru, and V. P. Brendel Common introns within orthologous genes: software and application to plants Brief Bioinform, November 1, 2009; 10(6): 631 - 644. [Abstract] [Full Text] [PDF] |
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S. Cook, G. Moureau, R. E. Harbach, L. Mukwaya, K. Goodger, F. Ssenfuka, E. Gould, E. C. Holmes, and X. de Lamballerie Isolation of a novel species of flavivirus and a new strain of Culex flavivirus (Flaviviridae) from a natural mosquito population in Uganda J. Gen. Virol., November 1, 2009; 90(11): 2669 - 2678. [Abstract] [Full Text] [PDF] |
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J. Giacomotto, C. Pertl, C. Borrel, M. C. Walter, S. Bulst, B. Johnsen, D. L. Baillie, H. Lochmuller, C. Thirion, and L. Segalat Evaluation of the therapeutic potential of carbonic anhydrase inhibitors in two animal models of dystrophin deficient muscular dystrophy Hum. Mol. Genet., November 1, 2009; 18(21): 4089 - 4101. [Abstract] [Full Text] [PDF] |
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D. Carstensen, J. Laudien, F. Leese, W. Arntz, and C. Held Genetic variability, shell and sperm morphology suggest that the surf clams Donax marincovichi and D. obesulus are one species J. Mollus. Stud., November 1, 2009; 75(4): 381 - 390. [Abstract] [Full Text] [PDF] |
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M. E. Rumpho, S. Pochareddy, J. M. Worful, E. J. Summer, D. Bhattacharya, K. N. Pelletreau, M. S. Tyler, J. Lee, J. R. Manhart, and K. M. Soule Molecular Characterization of the Calvin Cycle Enzyme Phosphoribulokinase in the Stramenopile Alga Vaucheria litorea and the Plastid Hosting Mollusc Elysia chlorotica Mol Plant, November 1, 2009; 2(6): 1384 - 1396. [Abstract] [Full Text] [PDF] |
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J. M. Flowers, Y. Hanzawa, M. C. Hall, R. C. Moore, and M. D. Purugganan Population Genomics of the Arabidopsis thaliana Flowering Time Gene Network Mol. Biol. Evol., November 1, 2009; 26(11): 2475 - 2486. [Abstract] [Full Text] [PDF] |
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M. Martinez, I. Cambra, L. Carrillo, M. Diaz-Mendoza, and I. Diaz Characterization of the Entire Cystatin Gene Family in Barley and Their Target Cathepsin L-Like Cysteine-Proteases, Partners in the Hordein Mobilization during Seed Germination Plant Physiology, November 1, 2009; 151(3): 1531 - 1545. [Abstract] [Full Text] [PDF] |
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A. De Wever, F. Leliaert, E. Verleyen, P. Vanormelingen, K. Van der Gucht, D. A. Hodgson, K. Sabbe, and W. Vyverman Hidden levels of phylodiversity in Antarctic green algae: further evidence for the existence of glacial refugia Proc R Soc B, October 22, 2009; 276(1673): 3591 - 3599. [Abstract] [Full Text] [PDF] |
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E. Desmond and S. Gribaldo Phylogenomics of Sterol Synthesis: Insights into the Origin, Evolution, and Diversity of a Key Eukaryotic Feature Gen Biol Evol, October 20, 2009; 2009(0): 364 - 381. [Abstract] [Full Text] [PDF] |
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J. S. Hawkins, S. R. Proulx, R. A. Rapp, and J. F. Wendel Rapid DNA loss as a counterbalance to genome expansion through retrotransposon proliferation in plants PNAS, October 20, 2009; 106(42): 17811 - 17816. [Abstract] [Full Text] [PDF] |
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E. Blasingame, T. Tuton-Blasingame, L. Larkin, A. M. Falick, L. Zhao, J. Fong, V. Vaidyanathan, A. Visperas, P. Geurts, X. Hu, et al. Pyriform Spidroin 1, a Novel Member of the Silk Gene Family That Anchors Dragline Silk Fibers in Attachment Discs of the Black Widow Spider, Latrodectus hesperus J. Biol. Chem., October 16, 2009; 284(42): 29097 - 29108. [Abstract] [Full Text] [PDF] |
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J. Jorda and A. V. Kajava T-REKS: identification of Tandem REpeats in sequences with a K-meanS based algorithm Bioinformatics, October 15, 2009; 25(20): 2632 - 2638. [Abstract] [Full Text] [PDF] |
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J. R. R. Whittle and T. U. Schwartz Architectural Nucleoporins Nup157/170 and Nup133 Are Structurally Related and Descend from a Second Ancestral Element J. Biol. Chem., October 9, 2009; 284(41): 28442 - 28452. [Abstract] [Full Text] [PDF] |
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E. Kazancioglu, T. J. Near, R. Hanel, and P. C. Wainwright Influence of sexual selection and feeding functional morphology on diversification rate of parrotfishes (Scaridae) Proc R Soc B, October 7, 2009; 276(1672): 3439 - 3446. [Abstract] [Full Text] [PDF] |
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S. Saha, K. H. Biswas, C. Kondapalli, N. Isloor, and S. S. Visweswariah The Linker Region in Receptor Guanylyl Cyclases Is a Key Regulatory Module: MUTATIONAL ANALYSIS OF GUANYLYL CYCLASE C J. Biol. Chem., October 2, 2009; 284(40): 27135 - 27145. [Abstract] [Full Text] [PDF] |
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M. Rastgou, M. K. Habibi, K. Izadpanah, V. Masenga, R. G. Milne, Y. I. Wolf, E. V. Koonin, and M. Turina Molecular characterization of the plant virus genus Ourmiavirus and evidence of inter-kingdom reassortment of viral genome segments as its possible route of origin J. Gen. Virol., October 1, 2009; 90(10): 2525 - 2535. [Abstract] [Full Text] [PDF] |
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R. A. Valverde and S. Sabanadzovic A novel plant virus with unique properties infecting Japanese holly fern J. Gen. Virol., October 1, 2009; 90(10): 2542 - 2549. [Abstract] [Full Text] [PDF] |
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D. S. Smyth and D. A. Robinson Integrative and Sequence Characteristics of a Novel Genetic Element, ICE6013, in Staphylococcus aureus J. Bacteriol., October 1, 2009; 191(19): 5964 - 5975. [Abstract] [Full Text] [PDF] |
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R. Schwarz, P. N. Seibel, S. Rahmann, C. Schoen, M. Huenerberg, C. Muller-Reible, T. Dandekar, R. Karchin, J. Schultz, and T. Muller Detecting species-site dependencies in large multiple sequence alignments Nucleic Acids Res., October 1, 2009; 37(18): 5959 - 5968. [Abstract] [Full Text] [PDF] |
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S. N. Gardner, A. L. Hiddessen, P. L. Williams, C. Hara, M. C. Wagner, and B. W. Colston Jr Multiplex primer prediction software for divergent targets Nucleic Acids Res., October 1, 2009; 37(19): 6291 - 6304. [Abstract] [Full Text] [PDF] |
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L. Leclere, P. Schuchert, C. Cruaud, A. Couloux, and M. Manuel Molecular Phylogenetics of Thecata (Hydrozoa, Cnidaria) Reveals Long-Term Maintenance of Life History Traits despite High Frequency of Recent Character Changes Syst Biol, October 1, 2009; 58(5): 509 - 526. [Abstract] [Full Text] [PDF] |
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K. M. Hamilton, P. W. Shaw, and D. Morritt Prevalence and seasonality of Hematodinium (Alveolata: Syndinea) in a Scottish crustacean community ICES J. Mar. Sci., October 1, 2009; 66(9): 1837 - 1845. [Abstract] [Full Text] [PDF] |
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E. Heytens, J. Parrington, K. Coward, C. Young, S. Lambrecht, S.-Y. Yoon, R.A. Fissore, R. Hamer, C.M. Deane, M. Ruas, et al. Reduced amounts and abnormal forms of phospholipase C zeta (PLC{zeta}) in spermatozoa from infertile men Hum. Reprod., October 1, 2009; 24(10): 2417 - 2428. [Abstract] [Full Text] [PDF] |
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C. Payen, G. Fischer, C. Marck, C. Proux, D. J. Sherman, J.-Y. Coppee, M. Johnston, B. Dujon, and C. Neuveglise Unusual composition of a yeast chromosome arm is associated with its delayed replication Genome Res., October 1, 2009; 19(10): 1710 - 1721. [Abstract] [Full Text] [PDF] |
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T. J. Sharpton, J. E. Stajich, S. D. Rounsley, M. J. Gardner, J. R. Wortman, V. S. Jordar, R. Maiti, C. D. Kodira, D. E. Neafsey, Q. Zeng, et al. Comparative genomic analyses of the human fungal pathogens Coccidioides and their relatives Genome Res., October 1, 2009; 19(10): 1722 - 1731. [Abstract] [Full Text] [PDF] |
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C. Kemena and C. Notredame Upcoming challenges for multiple sequence alignment methods in the high-throughput era Bioinformatics, October 1, 2009; 25(19): 2455 - 2465. [Abstract] [Full Text] [PDF] |
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H. Shan, L. Zahn, S. Guindon, P. K. Wall, H. Kong, H. Ma, C. W. dePamphilis, and J. Leebens-Mack Evolution of Plant MADS Box Transcription Factors: Evidence for Shifts in Selection Associated with Early Angiosperm Diversification and Concerted Gene Duplications Mol. Biol. Evol., October 1, 2009; 26(10): 2229 - 2244. [Abstract] [Full Text] [PDF] |
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M. Turmel, C. Otis, and C. Lemieux The Chloroplast Genomes of the Green Algae Pedinomonas minor, Parachlorella kessleri, and Oocystis solitaria Reveal a Shared Ancestry between the Pedinomonadales and Chlorellales Mol. Biol. Evol., October 1, 2009; 26(10): 2317 - 2331. [Abstract] [Full Text] [PDF] |
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B. Pils and A. Heyl Unraveling the Evolution of Cytokinin Signaling Plant Physiology, October 1, 2009; 151(2): 782 - 791. [Abstract] [Full Text] [PDF] |
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W. Hao and J. D. Palmer Fine-scale mergers of chloroplast and mitochondrial genes create functional, transcompartmentally chimeric mitochondrial genes PNAS, September 29, 2009; 106(39): 16728 - 16733. [Abstract] [Full Text] [PDF] |
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E. van den Born, A. Bekkelund, M. N. Moen, M. V. Omelchenko, A. Klungland, and P. O. Falnes Bioinformatics and functional analysis define four distinct groups of AlkB DNA-dioxygenases in bacteria Nucleic Acids Res., September 28, 2009; (2009) gkp774v1. [Abstract] [Full Text] [PDF] |
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L. J. Holt, B. B. Tuch, J. Villen, A. D. Johnson, S. P. Gygi, and D. O. Morgan Global Analysis of Cdk1 Substrate Phosphorylation Sites Provides Insights into Evolution Science, September 25, 2009; 325(5948): 1682 - 1686. [Abstract] [Full Text] [PDF] |
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C. C. Weber and L. D. Hurst Protein Rates of Evolution Are Predicted by Double-Strand Break Events, Independent of Crossing-over Rates Gen Biol Evol, September 23, 2009; 2009(0): 340 - 349. [Abstract] [Full Text] [PDF] |
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H.-Y. Chang, J. Hemp, Y. Chen, J. A. Fee, and R. B. Gennis The cytochrome ba3 oxygen reductase from Thermus thermophilus uses a single input channel for proton delivery to the active site and for proton pumping PNAS, September 22, 2009; 106(38): 16169 - 16173. [Abstract] [Full Text] [PDF] |
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V. E. Mayer and H. Voglmayr Mycelial carton galleries of Azteca brevis (Formicidae) as a multi-species network Proc R Soc B, September 22, 2009; 276(1671): 3265 - 3273. [Abstract] [Full Text] [PDF] |
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D. A. Caron, P. D. Countway, P. Savai, R. J. Gast, A. Schnetzer, S. D. Moorthi, M. R. Dennett, D. M. Moran, and A. C. Jones Defining DNA-Based Operational Taxonomic Units for Microbial-Eukaryote Ecology Appl. Envir. Microbiol., September 15, 2009; 75(18): 5797 - 5808. [Abstract] [Full Text] [PDF] |
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J. B. W. Wolf, A. Kunstner, K. Nam, M. Jakobsson, and H. Ellegren Nonlinear Dynamics of Nonsynonymous (dN) and Synonymous (dS) Substitution Rates Affects Inference of Selection Gen Biol Evol, September 4, 2009; 2009(0): 308 - 319. [Abstract] [Full Text] [PDF] |
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M. Kjos, I. F. Nes, and D. B. Diep Class II one-peptide bacteriocins target a phylogenetically defined subgroup of mannose phosphotransferase systems on sensitive cells Microbiology, September 1, 2009; 155(9): 2949 - 2961. [Abstract] [Full Text] [PDF] |
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P. T. Beernink and D. M. Granoff The modular architecture of meningococcal factor H-binding protein Microbiology, September 1, 2009; 155(9): 2873 - 2883. [Abstract] [Full Text] [PDF] |
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J. Oberto, N. Breuil, A. Hecker, F. Farina, C. Brochier-Armanet, E. Culetto, and P. Forterre Qri7/OSGEPL, the mitochondrial version of the universal Kae1/YgjD protein, is essential for mitochondrial genome maintenance Nucleic Acids Res., September 1, 2009; 37(16): 5343 - 5352. [Abstract] [Full Text] [PDF] |
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M. Savic, J. Lovric, T. I. Tomic, B. Vasiljevic, and G. L. Conn Determination of the target nucleosides for members of two families of 16S rRNA methyltransferases that confer resistance to partially overlapping groups of aminoglycoside antibiotics Nucleic Acids Res., September 1, 2009; 37(16): 5420 - 5431. [Abstract] [Full Text] [PDF] |
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Y.-Q. Shen, B. F. Lang, and G. Burger Diversity and dispersal of a ubiquitous protein family: acyl-CoA dehydrogenases Nucleic Acids Res., September 1, 2009; 37(17): 5619 - 5631. [Abstract] [Full Text] [PDF] |
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S. Chun and J. C. Fay Identification of deleterious mutations within three human genomes Genome Res., September 1, 2009; 19(9): 1553 - 1561. [Abstract] [Full Text] [PDF] |
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R. Reinheimer and E. A. Kellogg Evolution of AGL6-like MADS Box Genes in Grasses (Poaceae): Ovule Expression Is Ancient and Palea Expression Is New PLANT CELL, September 1, 2009; 21(9): 2591 - 2605. [Abstract] [Full Text] [PDF] |
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S.-K. Oh, C. Young, M. Lee, R. Oliva, T. O. Bozkurt, L. M. Cano, J. Win, J. I.B. Bos, H.-Y. Liu, M. van Damme, et al. In Planta Expression Screens of Phytophthora infestans RXLR Effectors Reveal Diverse Phenotypes, Including Activation of the Solanum bulbocastanum Disease Resistance Protein Rpi-blb2 PLANT CELL, September 1, 2009; 21(9): 2928 - 2947. [Abstract] [Full Text] [PDF] |
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M. Roettger, W. Martin, and T. Dagan A Machine-Learning Approach Reveals That Alignment Properties Alone Can Accurately Predict Inference of Lateral Gene Transfer from Discordant Phylogenies Mol. Biol. Evol., September 1, 2009; 26(9): 1931 - 1939. [Abstract] [Full Text] [PDF] |
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M. Csuros and I. Miklos Streamlining and Large Ancestral Genomes in Archaea Inferred with a Phylogenetic Birth-and-Death Model Mol. Biol. Evol., September 1, 2009; 26(9): 2087 - 2095. [Abstract] [Full Text] [PDF] |
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A. Kianianmomeni, K. Stehfest, G. Nematollahi, P. Hegemann, and A. Hallmann Channelrhodopsins of Volvox carteri Are Photochromic Proteins That Are Specifically Expressed in Somatic Cells under Control of Light, Temperature, and the Sex Inducer Plant Physiology, September 1, 2009; 151(1): 347 - 366. [Abstract] [Full Text] [PDF] |
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Y. Fong, J. Wakefield, and K. Rice Bayesian mixture modeling using a hybrid sampler with application to protein subfamily identification Biostat., August 20, 2009; (2009) kxp033v1. [Abstract] [Full Text] [PDF] |
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J. Wan, R. Griffiths, J. Ying, P. McCourt, and Y. Huang Development of Drought-Tolerant Canola (Brassica napus L.) through Genetic Modulation of ABA-mediated Stomatal Responses Crop Sci., August 7, 2009; 49(5): 1539 - 1554. [Abstract] [Full Text] [PDF] |
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T. Yang, L. Bar-Peled, L. Gebhart, S. G. Lee, and M. Bar-Peled Identification of Galacturonic Acid-1-phosphate Kinase, a New Member of the GHMP Kinase Superfamily in Plants, and Comparison with Galactose-1-phosphate Kinase J. Biol. Chem., August 7, 2009; 284(32): 21526 - 21535. [Abstract] [Full Text] [PDF] |
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H. Liu, I. Probert, J. Uitz, H. Claustre, S. Aris-Brosou, M. Frada, F. Not, and C. de Vargas Extreme diversity in noncalcifying haptophytes explains a major pigment paradox in open oceans PNAS, August 4, 2009; 106(31): 12803 - 12808. [Abstract] [Full Text] [PDF] |
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D. L. Adelson, J. M. Raison, and R. C. Edgar Characterization and distribution of retrotransposons and simple sequence repeats in the bovine genome PNAS, August 4, 2009; 106(31): 12855 - 12860. [Abstract] [Full Text] [PDF] |
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J. Zielonka, I. G. Bravo, D. Marino, E. Conrad, M. Perkovic, M. Battenberg, K. Cichutek, and C. Munk Restriction of Equine Infectious Anemia Virus by Equine APOBEC3 Cytidine Deaminases J. Virol., August 1, 2009; 83(15): 7547 - 7559. [Abstract] [Full Text] [PDF] |
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W. F. Fricke, T. J. Welch, P. F. McDermott, M. K. Mammel, J. E. LeClerc, D. G. White, T. A. Cebula, and J. Ravel Comparative Genomics of the IncA/C Multidrug Resistance Plasmid Family J. Bacteriol., August 1, 2009; 191(15): 4750 - 4757. [Abstract] [Full Text] [PDF] |
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Z. Wunderlich and L. A. Mirny Using genome-wide measurements for computational prediction of SH2-peptide interactions Nucleic Acids Res., August 1, 2009; 37(14): 4629 - 4641. [Abstract] [Full Text] [PDF] |
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M. E. Siddall, F. M. Fontanella, S. C. Watson, S. Kvist, and C. Erseus Barcoding Bamboozled by Bacteria: Convergence to Metazoan Mitochondrial Primer Targets by Marine Microbes Syst Biol, August 1, 2009; 58(4): 445 - 451. [Full Text] [PDF] |
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N. C. Sheffield, H. Song, S. L. Cameron, and M. F. Whiting Nonstationary Evolution and Compositional Heterogeneity in Beetle Mitochondrial Phylogenomics Syst Biol, August 1, 2009; 58(4): 381 - 394. [Abstract] [Full Text] [PDF] |
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C.-H. Kuo, N. A. Moran, and H. Ochman The consequences of genetic drift for bacterial genome complexity Genome Res., August 1, 2009; 19(8): 1450 - 1454. [Abstract] [Full Text] [PDF] |
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F. Zhao, J. Qi, and S. C. Schuster Tracking the past: Interspersed repeats in an extinct Afrotherian mammal, Mammuthus primigenius Genome Res., August 1, 2009; 19(8): 1384 - 1392. [Abstract] [Full Text] [PDF] |
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B. Jacobs, F. Lens, and E. Smets Evolution of fruit and seed characters in the Diervilla and Lonicera clades (Caprifoliaceae, Dipsacales) Ann. Bot., August 1, 2009; 104(2): 253 - 276. [Abstract] [Full Text] [PDF] |
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J. H. Fong and A. Marchler-Bauer CORAL: aligning conserved core regions across domain families Bioinformatics, August 1, 2009; 25(15): 1862 - 1868. [Abstract] [Full Text] [PDF] |
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A. F. Neuwald Rapid detection, classification and accurate alignment of up to a million or more related protein sequences Bioinformatics, August 1, 2009; 25(15): 1869 - 1875. [Abstract] [Full Text] [PDF] |
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R. Gouveia-Oliveira, F. S. Roque, R. Wernersson, T. Sicheritz-Ponten, P. W. Sackett, A. Molgaard, and A. G. Pedersen InterMap3D: predicting and visualizing co-evolving protein residues Bioinformatics, August 1, 2009; 25(15): 1963 - 1965. [Abstract] [Full Text] [PDF] |
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W. Hao and G. B. Golding Does Gene Translocation Accelerate the Evolution of Laterally Transferred Genes? Genetics, August 1, 2009; 182(4): 1365 - 1375. [Abstract] [Full Text] [PDF] |
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S. T. Mugford, X. Qi, S. Bakht, L. Hill, E. Wegel, R. K. Hughes, K. Papadopoulou, R. Melton, M. Philo, F. Sainsbury, et al. A Serine Carboxypeptidase-Like Acyltransferase Is Required for Synthesis of Antimicrobial Compounds and Disease Resistance in Oats PLANT CELL, August 1, 2009; 21(8): 2473 - 2484. [Abstract] [Full Text] [PDF] |
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C. Staiger, A. Hinneburg, and R. B. Klosgen Diversity in Degrees of Freedom of Mitochondrial Transit Peptides Mol. Biol. Evol., August 1, 2009; 26(8): 1773 - 1780. [Abstract] [Full Text] [PDF] |
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J. R.P.M. Strating, N. H.M. van Bakel, J. A.M. Leunissen, and G. J.M. Martens A Comprehensive Overview of the Vertebrate p24 Family: Identification of a Novel Tissue-Specifically Expressed Member Mol. Biol. Evol., August 1, 2009; 26(8): 1707 - 1714. [Abstract] [Full Text] [PDF] |
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R. P. Meisel, M. V. Han, and M. W. Hahn A Complex Suite of Forces Drives Gene Traffic from Drosophila X Chromosomes Gen Biol Evol, July 31, 2009; 2009(0): 176 - 188. [Abstract] [Full Text] [PDF] |
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