quadgram

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quadgram frequency
copyright holder for this1337
is the author funder1337
the copyright holder for1337
certified by peer review1328
was not certified by1259
which was not certified1259
not certified by peer1250
holder for this preprintthis1250
for this preprintthis version1250
preprintthis version posted january1250
this preprintthis version posted1250
com b m kdl887
the preprint in perpetuity877
who has granted biorxiv877
granted biorxiv a license877
to display the preprint877
display the preprint in877
has granted biorxiv a877
biorxiv a license to877
a license to display877
license to display the877
no reuse allowed without448
reuse allowed without permission448
international licenseavailable under a435
it is made the435
is made the copyright435
made the copyright holder435
international licensemade available under355
it is the copyright355
licensemade available under a355
is the copyright holder355
com b h ctd265
b m kdl qaa106
m kdl qaa http106
com b m zzqk101
b m kdl gtt92
m kdl gtt http91
m kdl jg a89
holder for this preprint87
is made available under87
it is made available87
kdl jg a http84
b m kdl jg84
was notthis version posted78
which was notthis version78
made available under the78
international licensea certified by78
available under the copyright78
licensea certified by peer78
under the copyright holder78
notthis version posted january78
com c h ctd75
m kdl lmi h75
b m kdl lmi74
kdl lmi h http74
b m kdl bijvc70
m kdl bijvc http70
i i i i69
b m kdl vecw67
m kdl vecw http67
b m kdl ahwg64
m kdl ahwg http64
b m kdl udus57
m kdl udus http57
m kdl wfrst http56
b m kdl wfrst56
m kdl xp y56
m kdl sj we54
b m kdl xp52
b m kdl sj52
kdl sj we http52
kdl xp y http52
b m kdl isag49
m kdl isag http49
ta t re l45
ps ta t re45
the mammalian methylation array44
can be used to37
data was obtained from35
for m enrich seq35
the total number of33
m o i ifnl32
m kdl vjim http32
b m kdl vjim32
on the other hand31
h h h h28
with hbv integration sequences27
min ps ta t27
in the context of26
time min ps ta26
com c m zzqk25
m o i m25
with each two technical25
each two technical replicates25
thiamine c h o23
com c m kdl23
i m o i22
o i m o22
deephbv with hbv integration22
in the case of22
electronic health care records21
as well as the21
for each of the21
with respect to the21
is the number of20
r ef s eq20
the number of mismatches20
of stat and stat20
b m kdl xpakk20
a wide range of20
ta t r el19
journal of statistical software19
m kdl xpakk http19
of downstream sequence to19
to the number of18
the size of the18
and the number of18
of the edited cytidine18
com storage browser brain18
m fi ps ta17
a b c d17
fi ps ta t17
ta bl et s17
prescriptions in electronic health17
after stimulation with il17
in electronic health care17
ps ta t r17
drug prescriptions in electronic17
m fi time min16
m g ta bl16
g ta bl et16
com work bibliography http16
were obtained from the16
p a tie n16
a large number of16
enrich seq rienrich seq15
natl acad sci u15
this work was supported15
an r package for15
the expression levels of15
the scalar curvature of15
acad sci u s15
e a lth y15
sci u s a15
polya selection gse sars15
h e a lth15
b h ctd n15
used in this study15
m enrich seq rienrich15
analysing drug prescriptions in15
severe acute respiratory syndrome15
on the basis of14
a tie n t14
to be associated with14
work was supported by14
to two molecules of14
bound to two molecules14
is available at https14
in terms of the14
the second fundamental form14
proc natl acad sci14
the performance of the14
dimer bound to two14
and galiez et al14
p r s s13
most frequently recurring genes13
mock mock mock h13
to the most frequently13
o i ifnl sars13
the extent to which13
was obtained from three13
and columns represent cancer13
gse mock mock mock13
the length of the13
columns represent cancer types13
of the predicted atus13
l c x c13
of the number of13
can be found in13
c x c l13
c l c x13
m enrich seq and13
i i i preprint13
tm p r s13
correspond to the most13
m kdl m hq13
the most frequently recurring13
is one of the13
made available for use12
u mrna editing sites12
y s stat p12
also made available for12
in the number of12
a us government work12
replicates with each two12
is a us government12
use under a cc12
mock mock h homo12
this article is a12
under a cc license12
is also made available12
was supported by the12
mock h homo sapiens12
under usc the copyright12
b m kdl m12
general classification general ccn12
human bronchial epithelial cells12
available for use under12
subject to copyright under12
based on perfect matching12
copyright under usc the12
is not subject to12
x c l c12
for use under a12
we found that the12
classification general ccn score12
rows correspond to the12
to copyright under usc12
x x x x12
biological replicates with each12
usc the copyright holder12
it is not subject12
b c d e12
article is a us12
and is also made12
not subject to copyright12
as a function of11
as shown in figure11
valid read pairs per11
log nm ps ta11
kdl m hq http11
polya selection gse mock11
the sum of the11
association of editing frequency11
cells infected with sars11
the accuracy of the11
number of mismatches for11
latex r e https11
p v al u11
university school of medicine11
of editing frequency with11
selection gse mock mock11
phage and host sequences11
log p v al11
nm ps ta t11
scalar curvatures computed for11
v al u e11
b h ctd q10
the structure of the10
heterotypic and homotypic multiplets10
t h t h10
the overlapping cell lines10
the true value of10
end genes of the10
dimer bound to stat10
the global length scale10
change of three biological10
the gene expression profile10
sequences tcga pan cancer10
k valid read pairs10
the number of species10
su br ea d10
at the same time10
n ai ve c10
two molecules of stat10
the two refseq annotations10
of three biological replicates10
from three biological replicates10
public research allele frequency10
the number of cells10
obtained from three biological10
ai ve c d10
as part of the10
e ns em bl10
acute respiratory syndrome coronavirus10
fold change of three10
may be due to10
of the cell types10
as shown in the10
it is possible to10
gene was annotated by9
national academy of sciences9
ai c index https9
we were able to9
as a driver within9
expression levels of the9
journal of vegetation science9
within cells indicate that9
chasmplus as a driver9
primary human bronchial epithelial9
available under a the9
it can be seen9
on the mammalian methylation9
fi time min ps9
b h ctd k9
of the cell lines9
sequence to per unit9
genes of the predicted9
cells indicate that the9
b bnwyax odthp http9
downstream sequence to per9
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driver within a given9
vs r ef s9
was obtained from two9
for each cell line9
of the national academy9
within a given tcga9
a given tcga cohort9
a ci containing the9
p b m c9
for the analysis of9
b a l f9
with at least one9
marks within cells indicate9
annotated by chasmplus as9
n points uniformly sampled9
the number of cell9
fold induction log p9
seq and rienrich seq9
contributed equally to this9
red marks within cells9
all eur amr sas9
predicted atus by seqatu9
hbv integration sequences tcga9
peerthis version posted january9
of each cell type9
equally to this work9
see figure s a9
t p m ifnl9
ranked by fraction of9
eur amr sas afr9
by fraction of samples9
amr sas afr eas9
for each cell type9
can be seen from9
integration sequences tcga pan9
the number of reads9
downstream of the edited9
enrich seq and rienrich9
the national academy of9
induction log p v9
l u n g9
points uniformly sampled from9
by chasmplus as a9
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a the copyright holder9
peripheral blood mononuclear cells9
certified by peerthis version9
a driver within a9
to per unit increments9
in health and disease9
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not certified by peerthis9
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n h b e9
by the number of9
nodes u and v9
made available under a9
under a the copyright9
was annotated by chasmplus9
it is important to9
theory of resistant biomolecules9
by peerthis version posted9
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com b bnwyax bifqg8
the gene was annotated8
bnwyax hbt j http8
ac e c ac8
m o i ifnb8
m zzqk q l8
bound to stat via8
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com b bnwyax thhr8
bnwyax q esm http8
b bnwyax wm a8
the single cell data8
h homo sapiens a8
ir f ir f8
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bnwyax wm a http8
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kgp cohort dv glnexus8
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h ctd ndo a8
node and edge annotation8
c c l c8
area under the curve8
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authors contributed equally to8
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the fraction of samples8
bnwyax z a http8
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in the human population8
both homotypic and heterotypic8
com b bnwyax kxhhl8
b bnwyax dctjj http8
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dv glnexus opt v8
unknown general classification general8
curvatures computed for the8
on the mammalian array8
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bnwyax g buj http8
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by deepmm and phenix8
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of gene expression in8
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ranked by binomial p8
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b bnwyax assl http8
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b bnwyax o i8
in ecology and evolution8
bnwyax o i http8
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dimer bound to pstat8
public research cohort kgp8
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b bnwyax eqqvf http8
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h homo sapiens calu8
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n c b i8
cohort kgp cohort dv8
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satellite glia and endothelial8
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al u h m8
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com b bnwyax wm8
tl r tl r8
the relationship between the8
e ve ro e8
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c al u h8
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c n h b8
c ac o c8
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ro e lo g8
h m r c8
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the number of classifications8
one of the most8
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b bnwyax g buj8
ac o c al8
com b bnwyax e8
b e ve ro8
el l l in8
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com b bnwyax shsw8
genomic and transcriptomic data8
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correlation with environmental distance8
com b bnwyax o8
research cohort kgp cohort8
the image patch dataset8
b bnwyax shsw http8
for the original dataset8
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studies have shown that8
bnwyax e ooj http8
b bnwyax kxhhl http8
m r c n8
o c al u8
bnwyax uh g http8
h b e ve8
this dataset we downloaded8
com b bnwyax eqqvf8
compared with reshuffled controls8
cohort dv glnexus opt8
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com b bnwyax wfsum8
c el l l8
the performance of sclapa8
cancer cell line encyclopedia8
the broad and sanger7
allele frequency pretrained model7
uniform read distribution along7
included in this study7
from the figure that7
matching for m enrich7
quadruplex and triplex motifs7
ld c ha ng7
b bnwyax ymsj http7
is the set of7
homotypic and heterotypic multiplets7
not present in the7
in the other dataset7
b bnwyax karn http7
with the number of7
h ctd jlne http7
used to evaluate the7
recurrently disrupted by variants7
the expression level of7
of common essential genes7
for recurrently disrupted genes7
b bnwyax jkgi http7
major cell type clusters7
h ctd s lm7
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genome atlas research network7
r tl r tl7
of machine learning research7
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these authors contributed equally7
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of gene expression and7
in response to il7
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h ctd k rob7
recurrently disrupted genes in7
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y stat a p7
disrupted genes in each7
national institutes of health7
seen from the figure7
the average mutual information7
bnwyax ax xh http7
four out of five7
supported by the national7
results of analysis for7
research allele frequency pretrained7
in regulatory sequence motif7
distribution of gof p7
predicting response to chemotherapy7
of analysis for recurrently7
fo ld c ha7
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the start of the7
genes recurrently disrupted by7
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o i tp m7
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on the same date7
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b m zzqk q7
of mismatches for each7
m zzqk xjeg http7
in the r package7
of the royal society7
r s s tm7
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read distribution along mrna7
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mismatches in mooring sequence7
zzqk q l http7
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number of mismatches in7
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na na na na7
an exon skipping event7
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the percentage of the7
distribution along mrna transcripts7
ct iv e ge7
the edwards et al7
probability of severe illness7
fi c log nm7
s c o re7
mean and standard deviation7
ub cl on al7
or infected with sars7
oligonucleotide compositions of sars7
m o i tp7
small cell lung cancer7
of effective gene lengths7
each pair of annotations7
the number of sequences7
washington university school of7
analysis for recurrently disrupted7
b bnwyax as lx7
s tm p r7
a stop codon when7
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prediction accuracy of phirbo7
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iv e ge ne7
association with editing frequency7
b h ctd jlne7
from left to right7
h ctd crk v7
s ub cl on7
bnwyax as lx http7
the quality of the7
l c c l7
m zzqk n pa7
c ha ng e7
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cancer type of interest7
ne le ng th7
m fi c log7
s s tm p7
c l c c7
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stat activation by il7
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cells stimulated with il7
location of the edited7
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as ranked by fraction7
in the analysis of7
for a total of7
f ir f ir7
t t t t7
com b bnwyax ax7
cancer genome atlas research7
provided in supplementary table7
the true scalar curvature6
upstream and nucleotides downstream6
for islet and islet6
the department of automation6
b m zzqk meu6
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genetically engineered mouse models6
gender prop gender gender6
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levels of the top6
ami gender ami gender6
of maximal atu clusters6
interests the authors declare6
h ctd hn t6
experiment with each two6
the single cell reference6
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h ctd jqzsb http6
using the default splice6
ri ty s c6
the number of samples6
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of hbv integration sites6
with an exon skipping6
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apolipoprotein b mrna editing6
for pbmc and pbmc6
of points in the6
shown in figure b6
p s ta t6
gu la te d6
acid and secondary structure6
prediction of response to6
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the end of the6
c h n o6
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ctd n kax http6
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expression levels of ifns6
b h ctd crk6
the edited cytidine in6
ta t m fi6
representative experiment with each6
nucleotides upstream and nucleotides6
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the computed scalar curvatures6
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phosphorylated stat and stat6
an important role in6
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hbv integration sequences repeat6
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dissimilarity and environmental distance6
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c o re interaction6
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models built by deepmm6
and scnn g in6
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cancer type specific grn6
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no rm al iz6
c log nm ps6
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splice variant window parameter6
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g ef fe ct6
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default splice variant window6
the ms use case6
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h ctd cq b6
in male and female6
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the ucsc genome browser6
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the expected number of6
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out of five cancer6
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tcga pan cancer peaks6
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co ef fic ie6
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parent ngsc di pbmc6
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experiments with each two6
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average power plot and6
our results suggest that6
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the default splice variant6
for the image patches6
accuracy of the model6
of response to chemotherapy6
zzqk n pa http6
parameters for curvature estimation6
prop gender prop gender6
deletion bps associated with6
b h ctd ndo6
one representative experiment with6
h ctd gyl http6
b m zzqk ld6
b m zzqk njch6
of five cancer types6
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cpgs on the mammalian6
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correspondence should be addressed6
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bound to pstat via6
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u m a p6
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hidden subpopulations of cells6
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amino acid and secondary6
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single gene mrna transcripts6
ty s c o6
the number of patients6
rm al iz at6
average number of mismatches6
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of the image patches6
s im ila ri6
based on the digraph6
in the human genome6
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automation in xiamen university6
c j i pi6
journal of machine learning6
du ct io n6
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tablet oral mg tablet5
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relatively flat average mutual5
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the cancer genome atlas5
apa isoforms and genes5
by whether they were5
we compared the performance5
the receiver operating characteristic5
b m zzqk sfn5
optimum expression combination of5
sapiens calu polya selection5
the ensembl annotation contains5
n g t p5
c d t h5
h ctd lmbav http5
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posterior distributions for the5
b m zzqk nhfw5
have been shown to5
h ctd gwpe http5
h ctd cclhp http5
the difference between the5
we uniformly sampled n5
b h ctd wqpb5
are conditionally essential in5
it is known that5
b h ctd qanj5
the posterior distributions for5
as described in the5
and secondary structure types5
greater than that of5
were downloaded from the5
classifier when applied to5
the number of predicted5
we did not observe5
using the giab v5
regulatory sequence motif d5
are plotted against the5
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b h ctd me5
cgc as an oncogene5
h ctd wqpb http5
m o i ve5
vero e polya selection5
it is necessary to5
l n k m5
the scalar curvature is5
for the pbmc dataset5
b h ctd lmbav5
the number of genes5
and phase difference image5
c m kdl jg5
which have been contained5
our results show that5
belonging to the same5
were mock treated or5
each of the three5
are more likely to5
nucleotides surrounding the edited5
venlafaxine propranolol lisinopril atenolol5
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models and bayesian inference5
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contour lines indicate significance5
by their alignment scores5
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segmentation and motion estimation5
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gq and triplex motifs5
scalar curvatures were computed5
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roadmap epigenomics consortium et5
ci containing the true5
gradient boosted decision trees5
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seq data of balf5
oncogene and tumor suppressor5
in the ace spike5
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stat and stat activation5
the same neighborhood sizes5
ct io n time5
of genes in the5
times greater than that5
the ensembl and refseq5
the apolipoprotein b mrna5
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the sum of all5
on the gene expression5
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the splice junction region5
the pacific biosciences sequel5
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the utility of the5
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scalar curvature of k5
sequences flagged by coil5
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moderate and severe covid5
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cell rna sequencing data5
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is the sum of5
and tumor suppressor gene5
the riemannian curvature tensor5
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the ace spike interaction5
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methods in ecology and5
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the same cell type5
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pstat levels induced by5
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based prediction of response5
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expression combination of all5
journal of the american5
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they were annotated by5
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correlation coefficients for time5
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based on the disease5
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ethics approval and consent5
similarity learning and cell5
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an accurate and robust5
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different batch correction pipelines5
and gordon k smyth5
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cell lines more essential5
total number of reads5
gastrulation and brain datasets5
to assess the performance5
the protein data bank5
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and consent to participate5
their nominal tumor type5
cell type clustering and5
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improve the model performance4
the distribution of segment4
detecting multiplets in snatac4
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showing genes that are4
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gene expression profile alone4
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the median euclidean distance4
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the analytical scalar curvature4
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a fully supervised approach4
number of cells in4
inverse correlation with mls4
of the mammalian methylation4
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approach to curvature estimation4
a deep learning model4
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lagged data were used4
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pbmc and islet samples4
amygdala hypothalamus mammary root4
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to remove rrnas before4
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associations with editing frequency4
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associated with mtdna deletions4
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amino acid continuous encoding4
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frequency pretrained model wgs4
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the maximal atu clusters4
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inflexible groups such as4
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sapiens a polya selection4
base content of nucleotides4
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materials and methods data4
general ccn scores in4
positive patients type b4
general classification profiles of4
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periodicity in the distribution4
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gene regulatory network inference4
uniformly sampling n points4
three biological replicates with4
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glnexus opt v missing4
ngsc di pbmc https4
that the mammalian methylation4
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the use of the4
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supplementary table general classification4
on the mbrave platform4
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concentration of the species4
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gsea reactome pathway enrichment4
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the cytoplasmic domain of4
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and formulae are direct4
single gene mrna transcript4
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ctd k ci http4
was used to remove4
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hopkins university school of4
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the law of mass4
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initial concentrations in the4
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supplementary table subtype classification4
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estimates obtained by fitting4
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figure b shows the4
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based deep learning model4
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represents general ccn scores4
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the accuracy of rna4
patients with a prescription4
h ctd akii http4
genes that are differentially4
in different cell types4
improve the accuracy of4
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remove rrnas before sequencing4
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kinetics of stat activation4
the spike ace interaction4
expression and alternative polyadenylation4
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only to the model4
b h ctd cjaux4
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overlaid onto umap coordinates4
an adaptive learning approach4
predict hbv integration sites4
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the orientation of the4
deviations above the mean4
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and cell type clustering4
we also calculated the4
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sizes determined for the4
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derived from the same4
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hbv integration sequences as4
tumor types and subtypes4
number of mismatches over4
eas and afr populations4
clinical practice research datalink4
we next investigated whether4
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ovarian cancer cell lines4
perfect matching for m4
of mismatches over time4
variant is associated with4
more sustained stat phosphorylation4
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structures were manually added4
longer periodicity in the4
suggesting the outlines of4
negative association with editing4
for simulated em maps4
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set to be the4
between the three annotations4
on perfect matching for4
kinetics of irf protein4
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the performance of ccn4
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the highest ccn score4
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by uniformly sampling n4
b m c p4
phosphorylation kinetics of stat4
com b bnwyax d4
intergenic region bias rate4
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last month of the4
by the sequencing quality4
densely connected convolutional networks4
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to a quadratic over4
the first two principal4
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mismatches for each pcr4
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the entire cardiac cycle4
rates to the virus4
science foundation of china4
high grade serous ovarian4
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the selected time lags4
curvature of image patch4
the gene expression levels4
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cells stably expressing wt4
bnwyax e ooj https4
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sets from the abc4
the riemannian curvature of4
rpe cells stably expressing4
the distribution of the4
across different sizes of4
b h ctd gdid4
motifs compared with reshuffled4
gaussian noise of magnitude4
the sequencing quality control4
a l f p4
increasing the penalty parameter4
homo sapiens a polya4
h ctd gdid http4
the model under hypothesis4
with estimates obtained by4
m zzqk rjuf http4
patients with a first4
the preprocessed single cell4
b h ctd xd4
polya selection gse mers4
compute the scalar curvature4
m oc k m4
that the distribution of4
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can be set using4
genetic variants associated with4
solid red dots on4
canonical splicing patterns results4
preparation method polya selection4
u n g p4
see figure s c4
unbound cytoplasmic unphosphorylated stat4
b h ctd r4
after filtering for lowly4
a specific prescription event4
e m a tc4
the set of candidate4
and environment for statistical4
data were used for4
g p a tie4
polya selection was used4
a l f t4
p h il n4
an alignment file containing4
correlation between module score4
controls were generated by4
a single nucleotide variant4
m zzqk srq http4
hair and nonhair cells4
the first prescription event4
from allen mouse brain4
broad and sanger datasets4
od er at e4
phase difference in the4
the augmented image patch4
gene expression and alternative4
b h ctd xhkpd4
cyclical patterns in return4
staying around levels of4
obtained from two experiments4
a success rate of4
of average mutual information4
secretory unknown general classification4
subsites of the enzyme4
phage and host genomes4
the phase difference in4
set of experimental maps4
the top most variable4
h ctd cjaux http4
peptide fold change log4
clinical events before prescription4
for each cancer type4
p a c o4
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