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Spoken vocabulary outcomes of toddlers with DD (Walters et al., 2021) ...
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Spoken vocabulary outcomes of toddlers with DD (Walters et al., 2021) ...
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Spoken Vocabulary Outcomes of Toddlers With Developmental Delay After Parent-Implemented Augmented Language Intervention
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In: Am J Speech Lang Pathol (2021)
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Study of central exclusive [Image: see text] production in proton-proton collisions at [Formula: see text] and 13TeV
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In: Eur Phys J C Part Fields (2020)
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Intervention Focus Moderates the Association between Initial Receptive Language and Language Outcomes for Toddlers with Developmental Delay
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In: Augment Altern Commun (2019)
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The Relationship Between Speech, Language, and Phonological Awareness in Preschool-Age Children With Developmental Disabilities
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Visual-Graphic Symbol Acquisition in School Age Children with Developmental and Language Delays
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In: Augment Altern Commun (2018)
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Comparing the Effects of Speech-Generating Device Display Organization on Symbol Comprehension and Use by Three Children With Developmental Delays
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In: Am J Speech Lang Pathol (2017)
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Search for dark matter produced in association with heavy-flavor quark pairs in proton-proton collisions at [Formula: see text]
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Parent Stress and Perceptions of Language Development: Comparing Down Syndrome and Other Developmental Disabilities
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A Model of Phonological Processing, Language, and Reading for Students with Mild Intellectual Disability
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Acoustic and Perceptual Analyses of the Fundamental Frequencies of African American and Caucasian Males and Females
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In: ETD Archive (2012)
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Acoustic and Perceptual Analyses of the Fundamental Frequencies of African American and Caucasian Males and Females
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In: http://rave.ohiolink.edu/etdc/view?acc_num=csu1356126527 (2012)
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The role of verbal working memory in second language reading fluency and comprehension: A comparison of English and Korean
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In: http://www.pegem.net/dosyalar/dokuman/138538-20140106151120-5.pdf (2011)
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Contaminations in genomic sequences
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In: http://www.bioinf.uni-freiburg.de//Lehre/Theses/TP_videmp_summary.pdf (2011)
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Abstract:
Despite continued advances in whole genome sequencing techniques and the development of powerful assembly algorithms, newly sequenced genomes still often suffer from contaminations during the sequencing process. The most common sources of contamination are accessory DNAs deliberately attached to the DNA/RNA under investigation, including vectors, adapters, linkers and PCR primers. However, there are also unintended events, e.g. caused by transposon activity or simply impurities, leading to contaminated genomic sequences. These may then result in missassemblies of genomic sequences, meaningless analyses and potentially erroneous conclusions. However, no one knows to which extent publicly available genomes are contaminated. To encompass this unsatisfying situation we therefore plan to develop a comparative genomics approach to broadly identify contaminations in available genomic sequences. However there exist some tools those can find contaminations from adapters or from vectors alone. Here we present an approach based on machine learning to distinguish between contaminated and non-contaminated sequences instead of finding vector contaminations or adapter contaminations alone. As for now no such tool available, our approach would be foremost and showed promising results on different datasets. Key words: contamination, comparative genomics, vectors
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.415.1444 http://www.bioinf.uni-freiburg.de//Lehre/Theses/TP_videmp_summary.pdf
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