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f | 1 | { | f | 1 | { |
2 | "author": "Damianos P. Melidis", | 2 | "author": "Damianos P. Melidis", | ||
3 | "author_email": "damianosmel@gmail.com", | 3 | "author_email": "damianosmel@gmail.com", | ||
4 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 4 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
5 | "doi": "10.25835/0039431", | 5 | "doi": "10.25835/0039431", | ||
6 | "doi_date_published": "2020-10-03", | 6 | "doi_date_published": "2020-10-03", | ||
7 | "doi_publisher": "LUIS", | 7 | "doi_publisher": "LUIS", | ||
8 | "doi_status": "true", | 8 | "doi_status": "true", | ||
9 | "domain": "https://data.uni-hannover.de", | 9 | "domain": "https://data.uni-hannover.de", | ||
10 | "groups": [], | 10 | "groups": [], | ||
11 | "have_copyright": "Yes", | 11 | "have_copyright": "Yes", | ||
12 | "id": "cf1be2a3-5c87-4c23-9e97-6b76ba7dc26c", | 12 | "id": "cf1be2a3-5c87-4c23-9e97-6b76ba7dc26c", | ||
13 | "isopen": false, | 13 | "isopen": false, | ||
14 | "license_id": "CC-BY-SA-3.0", | 14 | "license_id": "CC-BY-SA-3.0", | ||
15 | "license_title": "CC-BY-SA-3.0", | 15 | "license_title": "CC-BY-SA-3.0", | ||
16 | "maintainer": "Damianos P. Melidis", | 16 | "maintainer": "Damianos P. Melidis", | ||
17 | "maintainer_email": "damianosmel@gmail.com", | 17 | "maintainer_email": "damianosmel@gmail.com", | ||
18 | "metadata_created": "2021-10-14T10:15:56.656892", | 18 | "metadata_created": "2021-10-14T10:15:56.656892", | ||
n | 19 | "metadata_modified": "2023-01-12T13:14:12.030651", | n | 19 | "metadata_modified": "2023-08-04T08:46:26.570818", |
20 | "name": "luh-dom2vec_pretrained", | 20 | "name": "luh-dom2vec_pretrained", | ||
21 | "notes": "Pre-trained dom2vec protein domain embeddings used for | 21 | "notes": "Pre-trained dom2vec protein domain embeddings used for | ||
22 | downstream evaluation discussed in \r\n\"dom2vec: Capturing domain | 22 | downstream evaluation discussed in \r\n\"dom2vec: Capturing domain | ||
23 | structure and function using self-supervision on protein domain | 23 | structure and function using self-supervision on protein domain | ||
24 | architectures\" (bioRxiv manuscript: | 24 | architectures\" (bioRxiv manuscript: | ||
25 | ps://www.biorxiv.org/content/10.1101/2020.03.17.995498v2)).\r\n\r\nThe | 25 | ps://www.biorxiv.org/content/10.1101/2020.03.17.995498v2)).\r\n\r\nThe | ||
26 | domain embeddings were trained using the annotations of InterPro db | 26 | domain embeddings were trained using the annotations of InterPro db | ||
27 | version 75.0.\r\n\r\n", | 27 | version 75.0.\r\n\r\n", | ||
28 | "num_resources": 1, | 28 | "num_resources": 1, | ||
29 | "num_tags": 4, | 29 | "num_tags": 4, | ||
30 | "organization": { | 30 | "organization": { | ||
31 | "approval_status": "approved", | 31 | "approval_status": "approved", | ||
32 | "created": "2021-10-14T10:15:56.594472", | 32 | "created": "2021-10-14T10:15:56.594472", | ||
33 | "description": "# Forschungszentrum | 33 | "description": "# Forschungszentrum | ||
34 | L3S\r\n\r\nhttps://www.l3s.de/", | 34 | L3S\r\n\r\nhttps://www.l3s.de/", | ||
35 | "id": "00c8f767-81fd-41ae-9235-dd4d1d43221c", | 35 | "id": "00c8f767-81fd-41ae-9235-dd4d1d43221c", | ||
36 | "image_url": | 36 | "image_url": | ||
37 | "https://www.l3s.de/sites/default/files/L3S_Logo_NEU_small.jpg", | 37 | "https://www.l3s.de/sites/default/files/L3S_Logo_NEU_small.jpg", | ||
38 | "is_organization": true, | 38 | "is_organization": true, | ||
39 | "name": "l3s", | 39 | "name": "l3s", | ||
40 | "state": "active", | 40 | "state": "active", | ||
41 | "title": "L3S", | 41 | "title": "L3S", | ||
42 | "type": "organization" | 42 | "type": "organization" | ||
43 | }, | 43 | }, | ||
44 | "owner_org": "00c8f767-81fd-41ae-9235-dd4d1d43221c", | 44 | "owner_org": "00c8f767-81fd-41ae-9235-dd4d1d43221c", | ||
45 | "private": false, | 45 | "private": false, | ||
46 | "relationships_as_object": [], | 46 | "relationships_as_object": [], | ||
47 | "relationships_as_subject": [], | 47 | "relationships_as_subject": [], | ||
48 | "repository_name": "Leibniz University Hannover", | 48 | "repository_name": "Leibniz University Hannover", | ||
49 | "resources": [ | 49 | "resources": [ | ||
50 | { | 50 | { | ||
51 | "cache_last_updated": null, | 51 | "cache_last_updated": null, | ||
52 | "cache_url": null, | 52 | "cache_url": null, | ||
53 | "created": "2020-10-03T15:57:24.151184", | 53 | "created": "2020-10-03T15:57:24.151184", | ||
54 | "description": "# dom2vec pretrained embeddings\r\n \r\n* | 54 | "description": "# dom2vec pretrained embeddings\r\n \r\n* | ||
55 | version: from protein annotations of Interpro db version 75.0.\r\n* | 55 | version: from protein annotations of Interpro db version 75.0.\r\n* | ||
56 | domain annotations: non-redundant plus the GAP domains (for details | 56 | domain annotations: non-redundant plus the GAP domains (for details | ||
57 | see manuscript)\r\n* usage: please see the example downstream | 57 | see manuscript)\r\n* usage: please see the example downstream | ||
58 | evaluation steps at | 58 | evaluation steps at | ||
59 | ithub](https://github.com/damianosmel/dom2vec#downstream-evaluation)", | 59 | ithub](https://github.com/damianosmel/dom2vec#downstream-evaluation)", | ||
60 | "format": "tar.gz", | 60 | "format": "tar.gz", | ||
61 | "hash": "", | 61 | "hash": "", | ||
62 | "id": "1de03f40-e8f5-47e6-bb97-efa6823d6c86", | 62 | "id": "1de03f40-e8f5-47e6-bb97-efa6823d6c86", | ||
63 | "last_modified": "2020-10-03T15:57:24.112760", | 63 | "last_modified": "2020-10-03T15:57:24.112760", | ||
n | 64 | "metadata_modified": "2023-01-12T13:14:12.034271", | n | 64 | "metadata_modified": "2023-08-04T08:46:26.573961", |
65 | "mimetype": "application/x-tar", | 65 | "mimetype": "application/x-tar", | ||
66 | "mimetype_inner": null, | 66 | "mimetype_inner": null, | ||
67 | "name": "dom2vec_pretrained_interpro_v75", | 67 | "name": "dom2vec_pretrained_interpro_v75", | ||
68 | "package_id": "cf1be2a3-5c87-4c23-9e97-6b76ba7dc26c", | 68 | "package_id": "cf1be2a3-5c87-4c23-9e97-6b76ba7dc26c", | ||
69 | "position": 0, | 69 | "position": 0, | ||
70 | "resource_type": null, | 70 | "resource_type": null, | ||
71 | "size": 44440026, | 71 | "size": 44440026, | ||
72 | "state": "active", | 72 | "state": "active", | ||
73 | "url": | 73 | "url": | ||
74 | 97-efa6823d6c86/download/dom2vec_non_redundant_gap_interpro75.tar.gz", | 74 | 97-efa6823d6c86/download/dom2vec_non_redundant_gap_interpro75.tar.gz", | ||
75 | "url_type": "" | 75 | "url_type": "" | ||
76 | } | 76 | } | ||
77 | ], | 77 | ], | ||
t | t | 78 | "services_used_list": "", | ||
78 | "source_metadata_created": "2020-10-03T15:32:02.259053", | 79 | "source_metadata_created": "2020-10-03T15:32:02.259053", | ||
79 | "source_metadata_modified": "2022-01-20T10:59:08.514445", | 80 | "source_metadata_modified": "2022-01-20T10:59:08.514445", | ||
80 | "state": "active", | 81 | "state": "active", | ||
81 | "tags": [ | 82 | "tags": [ | ||
82 | { | 83 | { | ||
83 | "display_name": "bioinformatics", | 84 | "display_name": "bioinformatics", | ||
84 | "id": "3a3c638a-ecac-42bd-8441-44ca5ea70fe5", | 85 | "id": "3a3c638a-ecac-42bd-8441-44ca5ea70fe5", | ||
85 | "name": "bioinformatics", | 86 | "name": "bioinformatics", | ||
86 | "state": "active", | 87 | "state": "active", | ||
87 | "vocabulary_id": null | 88 | "vocabulary_id": null | ||
88 | }, | 89 | }, | ||
89 | { | 90 | { | ||
90 | "display_name": "embeddings", | 91 | "display_name": "embeddings", | ||
91 | "id": "e32667b2-fe5f-4f7d-a227-73a4fe5c5310", | 92 | "id": "e32667b2-fe5f-4f7d-a227-73a4fe5c5310", | ||
92 | "name": "embeddings", | 93 | "name": "embeddings", | ||
93 | "state": "active", | 94 | "state": "active", | ||
94 | "vocabulary_id": null | 95 | "vocabulary_id": null | ||
95 | }, | 96 | }, | ||
96 | { | 97 | { | ||
97 | "display_name": "protein_domains", | 98 | "display_name": "protein_domains", | ||
98 | "id": "a34ac5d0-6e56-43d9-8534-b80394c3e06e", | 99 | "id": "a34ac5d0-6e56-43d9-8534-b80394c3e06e", | ||
99 | "name": "protein_domains", | 100 | "name": "protein_domains", | ||
100 | "state": "active", | 101 | "state": "active", | ||
101 | "vocabulary_id": null | 102 | "vocabulary_id": null | ||
102 | }, | 103 | }, | ||
103 | { | 104 | { | ||
104 | "display_name": "proteins", | 105 | "display_name": "proteins", | ||
105 | "id": "d273ecfa-671d-40f3-89cc-180a86d4264b", | 106 | "id": "d273ecfa-671d-40f3-89cc-180a86d4264b", | ||
106 | "name": "proteins", | 107 | "name": "proteins", | ||
107 | "state": "active", | 108 | "state": "active", | ||
108 | "vocabulary_id": null | 109 | "vocabulary_id": null | ||
109 | } | 110 | } | ||
110 | ], | 111 | ], | ||
111 | "terms_of_usage": "Yes", | 112 | "terms_of_usage": "Yes", | ||
112 | "title": "dom2vec: Protein domain embeddings", | 113 | "title": "dom2vec: Protein domain embeddings", | ||
113 | "type": "vdataset", | 114 | "type": "vdataset", | ||
114 | "url": "https://data.uni-hannover.de/dataset/dom2vec_pretrained", | 115 | "url": "https://data.uni-hannover.de/dataset/dom2vec_pretrained", | ||
115 | "version": "InterPro v. 75.0" | 116 | "version": "InterPro v. 75.0" | ||
116 | } | 117 | } |