DNA shape features improve transcription factor binding site predictions in vivo Article Swipe
Anthony Mathelier
,
Beibei Xin
,
Tsu-Pei Chiu
,
Lin Yang
,
Remo Rohs
,
Wyeth W. Wasserman
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.7490/f1000research.1112965.1
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.7490/f1000research.1112965.1
Interactions of transcription factors (TFs) with DNA comprise a complex interplay between base-specific amino acid contacts and readout of DNA structure. Recent studies have highlighted the complementarity of DNA sequence and shape in modeling TF binding in vitro. Here, we have provided a comprehensive evaluation of in vivo datasets to assess the predictive power obtained by augmenting various DNA sequence-based models of TF binding sites (TFBSs) with DNA shape features (helix twist, minor groove width, propeller twist, and roll). Results from 400 human ChIP-seq datasets for 76 TFs show that combining DNA shape features with position-specific scoring matrix (PSSM) scores improves TFBS predictions. Improvement has also been observed using TF flexible models and a machine-learning approach using a binary encoding of nucleotides in lieu of PSSMs. Incorporating DNA shape information is most beneficial for E2F and MADS-domain TF families. Our findings indicate that incorporating DNA sequence and shape information benefits the modeling of TF binding under complex in vivo conditions.
Related Topics
Concepts
Computational biology
DNA binding site
DNA
Transcription factor
DNA sequencing
Biology
Binding site
Base pair
Complementary DNA
Genetics
Gene
Gene expression
Promoter
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.7490/f1000research.1112965.1
- OA Status
- green
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All OpenAlex metadata
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DNA shape features improve transcription factor binding site predictions in vivoWork title
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articleOpenAlex work type
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2016Year of publication
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2016-01-01Full publication date if available
- Authors
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Anthony Mathelier, Beibei Xin, Tsu-Pei Chiu, Lin Yang, Remo Rohs, Wyeth W. WassermanList of authors in order
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https://doi.org/10.7490/f1000research.1112965.1Publisher landing page
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greenOpen access status per OpenAlex
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https://doi.org/10.7490/f1000research.1112965.1Direct OA link when available
- Concepts
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Computational biology, DNA binding site, DNA, Transcription factor, DNA sequencing, Biology, Binding site, Base pair, Complementary DNA, Genetics, Gene, Gene expression, PromoterTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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20Other works algorithmically related by OpenAlex
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| referenced_works_count | 0 |
| abstract_inverted_index.a | 8, 41, 111, 115 |
| abstract_inverted_index.76 | 84 |
| abstract_inverted_index.TF | 34, 60, 107, 134, 150 |
| abstract_inverted_index.by | 53 |
| abstract_inverted_index.in | 32 |
| abstract_inverted_index.is | 127 |
| abstract_inverted_index.of | 1, 18, 27, 44, 59, 118, 121, 149 |
| abstract_inverted_index.to | 47 |
| abstract_inverted_index.we | 38 |
| abstract_inverted_index.400 | 79 |
| abstract_inverted_index.DNA | 6, 19, 28, 56, 65, 89, 124, 141 |
| abstract_inverted_index.E2F | 131 |
| abstract_inverted_index.Our | 136 |
| abstract_inverted_index.TFs | 85 |
| abstract_inverted_index.and | 16, 30, 75, 110, 132, 143 |
| abstract_inverted_index.for | 83, 130 |
| abstract_inverted_index.has | 102 |
| abstract_inverted_index.the | 25, 49, 147 |
| abstract_inverted_index.TFBS | 99 |
| abstract_inverted_index.acid | 14 |
| abstract_inverted_index.also | 103 |
| abstract_inverted_index.been | 104 |
| abstract_inverted_index.from | 78 |
| abstract_inverted_index.have | 23, 39 |
| abstract_inverted_index.most | 128 |
| abstract_inverted_index.show | 86 |
| abstract_inverted_index.that | 87, 139 |
| abstract_inverted_index.with | 5, 64, 92 |
| abstract_inverted_index.(TFs) | 4 |
| abstract_inverted_index.Here, | 37 |
| abstract_inverted_index.amino | 13 |
| abstract_inverted_index.human | 80 |
| abstract_inverted_index.minor | 70 |
| abstract_inverted_index.power | 51 |
| abstract_inverted_index.shape | 31, 66, 90, 125, 144 |
| abstract_inverted_index.sites | 62 |
| abstract_inverted_index.under | 152 |
| abstract_inverted_index.using | 106, 114 |
| abstract_inverted_index.(PSSM) | 96 |
| abstract_inverted_index.(helix | 68 |
| abstract_inverted_index.PSSMs. | 122 |
| abstract_inverted_index.Recent | 21 |
| abstract_inverted_index.assess | 48 |
| abstract_inverted_index.binary | 116 |
| abstract_inverted_index.groove | 71 |
| abstract_inverted_index.matrix | 95 |
| abstract_inverted_index.models | 58, 109 |
| abstract_inverted_index.roll). | 76 |
| abstract_inverted_index.scores | 97 |
| abstract_inverted_index.twist, | 69, 74 |
| abstract_inverted_index.width, | 72 |
| abstract_inverted_index.(TFBSs) | 63 |
| abstract_inverted_index.Results | 77 |
| abstract_inverted_index.between | 11 |
| abstract_inverted_index.binding | 35, 61, 151 |
| abstract_inverted_index.complex | 9, 153 |
| abstract_inverted_index.factors | 3 |
| abstract_inverted_index.readout | 17 |
| abstract_inverted_index.scoring | 94 |
| abstract_inverted_index.studies | 22 |
| abstract_inverted_index.various | 55 |
| abstract_inverted_index.ChIP-seq | 81 |
| abstract_inverted_index.approach | 113 |
| abstract_inverted_index.benefits | 146 |
| abstract_inverted_index.comprise | 7 |
| abstract_inverted_index.contacts | 15 |
| abstract_inverted_index.datasets | 46, 82 |
| abstract_inverted_index.encoding | 117 |
| abstract_inverted_index.features | 67, 91 |
| abstract_inverted_index.findings | 137 |
| abstract_inverted_index.flexible | 108 |
| abstract_inverted_index.improves | 98 |
| abstract_inverted_index.indicate | 138 |
| abstract_inverted_index.in lieu | 120 |
| abstract_inverted_index.in vivo | 45, 154 |
| abstract_inverted_index.modeling | 33, 148 |
| abstract_inverted_index.observed | 105 |
| abstract_inverted_index.obtained | 52 |
| abstract_inverted_index.provided | 40 |
| abstract_inverted_index.sequence | 29, 142 |
| abstract_inverted_index.combining | 88 |
| abstract_inverted_index.families. | 135 |
| abstract_inverted_index.interplay | 10 |
| abstract_inverted_index.propeller | 73 |
| abstract_inverted_index.augmenting | 54 |
| abstract_inverted_index.beneficial | 129 |
| abstract_inverted_index.evaluation | 43 |
| abstract_inverted_index.in vitro. | 36 |
| abstract_inverted_index.predictive | 50 |
| abstract_inverted_index.structure. | 20 |
| abstract_inverted_index.Improvement | 101 |
| abstract_inverted_index.MADS-domain | 133 |
| abstract_inverted_index.conditions. | 155 |
| abstract_inverted_index.highlighted | 24 |
| abstract_inverted_index.information | 126, 145 |
| abstract_inverted_index.nucleotides | 119 |
| abstract_inverted_index.Interactions | 0 |
| abstract_inverted_index.predictions. | 100 |
| abstract_inverted_index.Incorporating | 123 |
| abstract_inverted_index.base-specific | 12 |
| abstract_inverted_index.comprehensive | 42 |
| abstract_inverted_index.incorporating | 140 |
| abstract_inverted_index.transcription | 2 |
| abstract_inverted_index.sequence-based | 57 |
| abstract_inverted_index.complementarity | 26 |
| abstract_inverted_index.machine-learning | 112 |
| abstract_inverted_index.position-specific | 93 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5087735169 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I184942183 |
| citation_normalized_percentile |