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1 ed on independent data sets within a limited sequence space.
2 ith the latter being "movable" in amino acid sequence space.
3 ered DNA binding molecules across the entire sequence space.
4 s, but has limited access to vast amounts of sequence space.
5  each other to explore the maximum potential sequence space.
6  how frequently such regulators arise within sequence space.
7 istics remain to be discovered in unexplored sequence space.
8 itro mutagenesis and samples a large protein sequence space.
9 thm for between-array normalization to probe sequence space.
10 ctional determinants within the well-defined sequence space.
11 te a previously unexplored region of protein sequence space.
12 e causes behind the observed irregularity in sequence space.
13 e essentially infinite complexity of protein sequence space.
14 unctional DNA, RNA, and protein molecules in sequence space.
15 s understand the distribution of function in sequence space.
16 landscape, relating function to structure in sequence space.
17 er frequency across the entire span of phage sequence space.
18 r never seen in the Vibrio region of 5S rRNA sequence space.
19  a computational screen to search the entire sequence space.
20 not strong enough to offset the huge size of sequence space.
21 to achieve a rapid basic coverage of protein sequence space.
22 ncept to visualization is a multidimensional sequence space.
23 od of time without searching an enormous RNA sequence space.
24 ibution onto a two-dimensional projection of sequence space.
25 e essentially infinite complexity of protein sequence space.
26  from sparse sampling of a larger portion of sequence space.
27 bpopulations, which diffuse independently in sequence space.
28 n to chart the fitness landscapes in protein sequence space.
29 derive in vitro GR binding affinities across sequence space.
30 ominance of a single variant within a narrow sequence space.
31 s, enables high-throughput mapping of enzyme sequence space.
32 siting disordered or nonfunctional points in sequence space.
33 echanism through which HCV can explore novel sequence space.
34 ts and many targets uniformly distributed in sequence space.
35 eterious or lethal regions of the phenotypic sequence space.
36 e-based function annotation of novel protein sequence space.
37 antly constrains the adaptive exploration of sequence space.
38 at fitness landscapes can be translocated in sequence space.
39 the most comprehensive datasets on tolerated sequence space.
40 nbiased, as is the vast majority of possible sequence space.
41 efficiently obtain a certain coverage of the sequence-space.
42 leavage, thus preventing them from consuming sequencing space.
43 limited multiplexing, but obscures available sequencing space.
44  functional enrichment in regions of protein sequence space accessible by recombination and provide a
45 his is that protein design should define the sequence space accessible to a given structure, rather t
46 imensional protein structure that affect the sequence space accessible to the evolution of HIV-1.
47                     Predictions of tolerated sequence space afforded by the model provide insights in
48 ere, we show that our procedure converges in sequence space, albeit not to the native sequence of the
49  untapped window into the history of protein sequence space, allowing events of genetic code expansio
50 at are not obvious; using motifs rather than sequence space also reduces search times considerably.
51 loring only an infinitesimal fraction of the sequence space and by their use of parametric approximat
52  patterns that completely covers the natural sequence space and can capture functional and structural
53 m the distribution of functional variants in sequence space and epistasis between residues.
54  antibody maturation within the framework of sequence space and fitness landscapes.
55 d lambda use the same strategy for searching sequence space and have almost identical patterns of div
56 nherent abundance of functional genotypes in sequence space and how accessible those genotypes are to
57 M is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates th
58 cially constructed representatives of the GA sequence space and scan the phage-displayed recombinant
59 sequences, permitting greater exploration of sequence space and stable folding.
60 cture determination to explore novel protein sequence space and structure-based function annotation.
61 ses have, in recent years, been expanding in sequence space and substrate spectrum under the challeng
62 arity as an efficient strategy for searching sequence space and that the germline V gene families evo
63 ular eukaryotes due to the larger intergenic sequence space and the increased complexity in regulatio
64               Yet, current methods merge the sequence space and the structure space into a single spa
65 uilds two separate networks to represent the sequence space and the structure space.
66 cognized, yet our limited knowledge of viral sequence space and virus-host interactions precludes acc
67 ten aid in the discovery of global optima in sequence space and/or lessen the number of generations i
68 g increasingly important in exploring enzyme sequence-space and creating improved or novel enzymes.
69 aying antibody diversity relative to natural sequence space, and has been shown to have diagnostic an
70 any RNA molecules sampled at random from RNA sequence space, and on 30 biological RNA molecules.
71 out the clustering of functional proteins in sequence space, and provides a basis for interpreting th
72 ons are the unfathomable vastness of protein sequence space, and the difficulty in making direct phys
73 to characterize alternative histories in the sequence space around an ancient transcription factor, w
74 signed sequences represent an enlargement of sequence space around native sequences.
75 tral drift screens to achieve large jumps in sequence space as may be required for the deimmunization
76 constituting catalytically versatile hubs in sequence space as potential starting points for the acqu
77 ined library diversity explores a comparable sequence space as the donor-derived natural repertoire a
78 e a new approach to explore and quantify the sequence space associated with a given protein structure
79 lysis provides a basis for understanding the sequence space associated with CaM function and should h
80                            One way to access sequence space at a higher density would be to make use
81 chive records to obtain complete coverage of sequence space at several resolutions while hiding redun
82 ion of redox potential which occurs when all sequence space available through mutation at two positio
83  Third, these nucleation points restrict the sequence space available to the protein during evolution
84  with the test sequence by using a metric in sequence space based on nearest-neighbor connectivity.
85                        Clustering of protein sequence space based on sequence similarity helps organi
86 ables focusing of an scFv library in soluble sequence space before functional screening and thus can
87 h coding would have had in exploring a wider sequence space before translation became highly specific
88        Furthermore, a route through foldable sequence-space between the simple peptide motif and exta
89 y are thus not only a generic feature of RNA sequence space but are relevant for the molecular evolut
90 rojects are increasing structure coverage of sequence space but have not significantly expanded the p
91 r protein design can sample large regions of sequence space, but suffer from undersampling of conform
92 ely similar sequences to yield a covering of sequence space by a representative subset of sequences.
93                         Thus, exploration of sequence space by a viral genome (in this case an unsegm
94 rocesses to guide the search through protein sequence space by designing, constructing, and testing c
95 ese foldable sequences have been selected in sequence space by evolution.
96 d a simple method for exploring nucleic acid sequence space by nonhomologous random recombination (NR
97  for this particular aptamer, the functional sequence space can be represented as a rugged landscape
98  demonstrates that the functional portion of sequence space can be significantly expanded by epistasi
99 ctural clustering and motif detection in the sequence space can efficiently identify side chain motif
100 ng the density of functional biomolecules in sequence space, characterizing diversity in natural popu
101 vement in affinity by maximizing sampling of sequence space close to the original selected antibody m
102     These results suggest that the volume of sequence space compatible with a given protein fold is d
103            We obtain an approximation of the sequence space compatible with a protein by designing a
104 ltiple sequence alignment that describes the sequence space compatible with the structure of interest
105 ance between the sequences in the subsets of sequence space compatible with their structures.
106 sters (UniRef) speed similarity searches via sequence space compression by merging sequences that are
107   Nucleic acid polymers selected from random sequence space constitute an enormous array of catalytic
108  does not access a large fraction of protein sequence space corresponding to primarily nonconservativ
109 natorial strategy for accessing nucleic acid sequence space corresponding to proteins comprising sele
110 to observe how selective pressure shapes the sequence space covered by functional molecules.
111 ations of genotypes in the joint protein-DNA sequence space defined by an historical transition in TF
112 recombination zone" describes that region of sequence space-defined by the residues that will ultimat
113  We conclude that the position of a virus in sequence space defines its mutant spectrum, evolutionary
114           We observed that the subset of the sequence space derived by using our design procedure is
115 he actual historical paths taken through RNA sequence space during 5S rRNA evolution would have most
116 sign algorithms, which aim to search a large sequence space efficiently and thus cannot rely on tempo
117  each of the GPCR classes, well separated in sequence space, enables an integrated superfamily-wide a
118 sive conformational sampling is coupled with sequence space exploration so that binding preferences f
119 y be used to quantify the characteristics of sequence space for a chosen structure without explicitly
120 ts the extent to which the model may explore sequence space for a prescribed set of parameters.
121 zyme superfamily requires the exploration of sequence space for adaptation to a new substrate with re
122 CS systems by allowing one to quickly search sequence space for mutations or even entirely new sequen
123 f this information would allow one to search sequence space for mutations that can be used to systema
124 uires the ability to search large volumes of sequence space for proteins with specific structural or
125 lection or screening to search vast areas of sequence space for sets of mutations that provide insigh
126 ient can significantly enlarge the available sequence space for the emergence of catalytically active
127 a fitness landscape, exploring nearly all of sequence space, for short RNAs surviving selection in vi
128 tructural domains, or by short walks through sequence space from ancestral structures.
129  is approximately 200 amino acids removed in sequence space from the catalytic nucleophile.
130 ns to the core DNA binding domain, remote in sequence space from the site of mutation.
131 lity, proteins have wide latitude to explore sequence space, generating biophysical diversity and pot
132     De novo protein design explores the full sequence space, guided by the physical principles that u
133 ens of PAS domains across a broad section of sequence space have been solved, revealing a conserved t
134 on which 130,000 peptides chosen from random sequence space have been synthesized.
135 y-that serves as a determinant of entropy in sequence space, i.e., the ability of a protein to accept
136 from the original pool on the exploration of sequence space in a doped reselection experiment.
137 hput, limiting our ability to widely explore sequence space in a quantitative manner.
138 ccur multiple times in a local region of RNA sequence space in fact usually will be accepted in any s
139               It is shown that exploring the sequence space in the vicinity of the sequence with unkn
140 lp taxonomically identify 7-38% of 'unknown' sequence space in viromes.
141 ecies population has moved into a segment of sequence space in which the average fitness value is neu
142 nusual evolutionary strategy for sampling of sequence space in which the gene encoding an important e
143 sequence information, structure information, sequence space information and structure space informati
144 mmunity resource that organizes this unknown sequence space into 27 K high confidence protein cluster
145             The basic idea is to partition a sequence space into a set of subspaces using a partition
146 een optimal native structures, which divides sequence space into fast-folding, thermally stable famil
147                              Mapping protein sequence space is a difficult problem that necessitates
148       The dynamics of the population in this sequence space is consistent with an adaptive walk on an
149                                   The entire sequence space is explored by each HCV genotype and subt
150    In reality, the dimensionality of protein sequence space is higher (20(L)) and there may be higher
151                                          The sequence space is initially searched by Monte Carlo samp
152                                   The entire sequence space is interrogated simultaneously, and the a
153 ess diverse than the sequences, and that DNA sequence space is larger and more diverse than DNA struc
154 dy strongly supports the notion that peptide sequence space is rich in small peptides, which might be
155 lgorithm consists of an outer loop, in which sequence space is sampled by a Monte Carlo search with s
156 d that naturally occurring cyanophage genome sequence space is statistically clustered into discrete
157               Bacterial and archaeal isolate sequence space is still far from saturated, and future e
158 n and core gene sets and suggested that this sequence space is well-sampled.
159 st of the R domain has been free to drift in sequence space leading to a more star-like phylogeny tha
160 s suggests that the interdependencies in RNA sequence space may be more complex than currently apprec
161  that the heretofore neglected dimensions of sequence space may change our views on how proteins evol
162 ersity must be focused into those regions of sequence space most likely to yield well folded structur
163  elements with changes in the core half-site sequence, spacing nucleotide, and flanking nucleotides.
164 stigate the importance of the core half-site sequences, spacing nucleotide, flanking sequences, and o
165 r design procedure is similar in size to the sequence spaces observed in nature.
166                             Neighborhoods in sequence space of a given radius around an RNA molecule
167 ge can be overcome by (i) sampling the large sequence space of a given scaffold through a phage displ
168 tly represented by mutations in the combined sequence space of a set of epitopes within the viral gen
169            In addition, we have explored the sequence space of all beta-trefoil proteins and have det
170          We therefore explore the functional sequence space of bnAb C05, which targets the receptor-b
171                 We systematically mapped the sequence space of four key residues in the Escherichia c
172 oteins resulted in a readily visualizable 3D sequence space of globins, where several subfamilies and
173 computational model to predict the tolerated sequence space of HIV-1 protease reachable by single mut
174 primarily, and unintentionally, screened the sequence space of microRNA seeds instead of the intended
175 ional, structure-based method to predict the sequence space of peptides recognized by PDZ domains, on
176 s that describes the currently known natural sequence space of proteins, we have reannotated all of t
177 but remains a challenge because of the large sequence space of proteins.
178     We applied this selection to examine the sequence space of residues flanking the Nostoc punctifor
179 r N-degrons in the lysine (K)-asparagine (N) sequence space of the 14-residue peptides containing eit
180 ntly expand the collection of cas genes: the sequence space of the Cas9 family, the key player in the
181 ve sequence analysis was used to explore the sequence space of the RA motif within ribosomal RNAs in
182  a small library that encompasses the entire sequence space of two amino acids should be of use in ma
183 cted to compare experimental and theoretical sequence spaces of tetrameric proto-peptides.
184 strand relative to random coil structure and sequence spacing of Asp, Glu residues.
185  of open reading frames that distils protein sequence space on the basis of three inherent properties
186 er, these results suggest that the volume of sequence space optimal for a protein structure is surpri
187 ein superfamilies, these break new ground in sequence space: promiscuity now connects enzymes with on
188                               The additional sequence space provided by three base pairs allows for t
189  used to drive a Monte Carlo optimization in sequence space: random moves are either accepted or reje
190 ld be characterized by large "leaps" through sequence space rather than isolated point mutations, per
191 or engineering sequence pools that links RNA sequence space regions with corresponding structural dis
192 ays provide only a limited view of the large sequence space relevant to the ribozyme function.
193 ical diversity, success in unlocking protein sequence space remains elusive.
194 y a tiny fraction of the total amount of DNA sequence space represented by this division of life.
195 sition of these invalid intermediates in the sequence space, seven of the 30 possible paths consisted
196  underlying distribution of functions across sequence space shaped historical evolution.
197 osomal RNAs in order to define its canonical sequence space signature.
198 nce is strong enough to overcome the size of sequence space so that most native sequences are located
199 space are vastly smaller than the nucleotide sequence space, suggesting a new avenue for finding nove
200 uman genome is significantly more compact in sequence space than a random genome.
201 es, which were found to cover a more limited sequence space than HLA-A and -B molecules.
202         Second, ncRNAs command a much larger sequence space than proteins, and can therefore achieve
203  allows ssDNA viruses to access much broader sequence space than through nucleotide substitution and
204 netic system can explore the entire expanded sequence space that additional nucleotides create, a maj
205 s that high mutation rates unlock regions of sequence space that are enriched in positively coupled m
206 n performance were found to map a functional sequence space that correlated well with computational p
207 xperiments that significantly expand the BH3 sequence space that has been experimentally tested for i
208 d-backbone assumption severely restricts the sequence space that is accessible via design.
209                                 The enormous sequence space that is available from 20 amino acids pro
210                   How large is the volume of sequence space that is compatible with a given protein s
211 ctory of functional DHFR through its protein sequence space that lead to the diverged binding and cat
212 rn of connectivity of functional variants in sequence space that likely constrains PhoQ evolution.
213  study also demonstrates unexplored areas of sequence space that may be fruitful for genome mining.
214 ic recombination explores a unique subset of sequence space that promotes rapid molecular diversifica
215 ar structure is modeled as a random graph in sequence space (the so-called neutral network).
216 ity of these two activities within a defined sequence space, the complete set of all intermediate seq
217 ablished tool to explore confined regions in sequence space, the generation of functional hybrid prot
218 R Interface" displays predictive analyses in sequence space; the "CrystalPainter" maps evolutionary c
219 by helping organize this unknown metagenomic sequence space, they typically use only approximately 75
220 report a methodology that allows the peptide sequence space to be searched for self-assembling struct
221        These tools, which enable the peptide sequence space to be searched for supramolecular propert
222 e virus must traverse a fitness "barrier" in sequence space to escape the host's cytotoxic T-lymphocy
223 esent nomenclature, via a sequential path in sequence space to evaluate the effects of conservative h
224 high specificity are frequently connected in sequence space to more promiscuous variants that can ser
225 e chaperones promote a deeper exploration of sequence space to strengthen functional PPIs, and dimini
226 ncreasing fidelity, biasing random drifts in sequence space toward 'crystallization.' This region enc
227 e facilitated by following fitness slopes in sequence space underpinned by binding-induced conformati
228                           The exploration of sequence space was accelerated by increasing the mutatio
229                                    Since the sequence space was not completely sampled, higher affini
230 possesses a stable scaffold, a large jump in sequence space was performed by the further addition of
231                           In this simplified sequence space we explore the mutational path from one f
232 rcome the enormity of the potential Bcl-x(L) sequence space, we developed and applied a computational
233 es of RNA Diels-Alderases closely related in sequence space were obtained.
234 uide the conformational search of amino acid sequence space, where physicochemical packing is accommo
235 opulations of organisms tightly localized in sequence space, whereas at higher mutation rates, specie
236 qually parsimonious trajectories through RNA sequence space which connect two pairs of sequences that
237 r binding partners to explore regions of the sequence space which correspond to less stable proteins.
238  The tested peptides were mapped in the HVR1 sequence space, which was visualized as a network of 11,
239 nucleoprotein filament is used to search DNA sequence space within 3D domains of DNA, exploiting mult
240 ary approach was used to expand the testable sequence space within a peptide library of approximately
241 o maximize the use of available nucleic acid sequence space would have been crucial during the presum

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