simplify gigascience CSL

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citations.tsv

@@ -38,4 +38,4 @@ doi:10.1002/asi.20591	doi:10.1002/asi.20591	doi:10.1002/asi.20591	EfWvuSjX
 doi:10/br5zd3	doi:10/br5zd3	doi:10.1016/s0378-8733(03)00009-1	9dBDcARP
 doi:10.1145/1014052.1014135	doi:10.1145/1014052.1014135	doi:10.1145/1014052.1014135	HSmvOV9E
 raw:laplacian	raw:laplacian	raw:laplacian	1E6tdJtDz
-raw:inference	raw:inference	raw:inference	1EgqwD4S1
+doi:10.5821/dissertation-2117-95691	doi:10.5821/dissertation-2117-95691	doi:10.5821/dissertation-2117-95691	yCdaxPuq

manuscript.md

@@ -12,7 +12,7 @@ keywords:
 - bioinformatics
 - python
 lang: en-US
-date-meta: '2023-12-22'
+date-meta: '2023-12-28'
 author-meta:
 - Michael Zietz
 - Daniel S. Himmelstein
@@ -31,11 +31,11 @@ header-includes: |
   <meta name="citation_title" content="The probability of edge existence due to node degree: a baseline for network-based predictions" />
   <meta property="og:title" content="The probability of edge existence due to node degree: a baseline for network-based predictions" />
   <meta property="twitter:title" content="The probability of edge existence due to node degree: a baseline for network-based predictions" />
-  <meta name="dc.date" content="2023-12-22" />
-  <meta name="citation_publication_date" content="2023-12-22" />
-  <meta property="article:published_time" content="2023-12-22" />
-  <meta name="dc.modified" content="2023-12-22T22:21:26+00:00" />
-  <meta property="article:modified_time" content="2023-12-22T22:21:26+00:00" />
+  <meta name="dc.date" content="2023-12-28" />
+  <meta name="citation_publication_date" content="2023-12-28" />
+  <meta property="article:published_time" content="2023-12-28" />
+  <meta name="dc.modified" content="2023-12-28T15:56:58+00:00" />
+  <meta property="article:modified_time" content="2023-12-28T15:56:58+00:00" />
   <meta name="dc.language" content="en-US" />
   <meta name="citation_language" content="en-US" />
   <meta name="dc.relation.ispartof" content="Manubot" />
@@ -79,13 +79,13 @@ header-includes: |
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   <meta name="citation_pdf_url" content="https://greenelab.github.io/xswap-manuscript/manuscript.pdf" />
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+  <link rel="alternate" type="text/html" href="https://greenelab.github.io/xswap-manuscript/v/55ccf900e5d69b9defd93e7b4341ae2cf3612720/" />
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   <meta property="og:type" content="article" />
   <meta property="twitter:card" content="summary_large_image" />
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-  <meta property="twitter:image" content="https://github.com/greenelab/xswap-manuscript/raw/5f221146e87027c8bdaab577f90bb4b6afbf5292/thumbnail.png" />
+  <meta property="og:image" content="https://github.com/greenelab/xswap-manuscript/raw/55ccf900e5d69b9defd93e7b4341ae2cf3612720/thumbnail.png" />
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@@ -106,10 +106,10 @@ _A DOI-citable version of this manuscript is available at <https://doi.org/10.11
 
 <small><em>
 This manuscript
-([permalink](https://greenelab.github.io/xswap-manuscript/v/5f221146e87027c8bdaab577f90bb4b6afbf5292/))
+([permalink](https://greenelab.github.io/xswap-manuscript/v/55ccf900e5d69b9defd93e7b4341ae2cf3612720/))
 was automatically generated
-from [greenelab/xswap-manuscript@5f22114](https://github.com/greenelab/xswap-manuscript/tree/5f221146e87027c8bdaab577f90bb4b6afbf5292)
-on December 22, 2023.
+from [greenelab/xswap-manuscript@55ccf90](https://github.com/greenelab/xswap-manuscript/tree/55ccf900e5d69b9defd93e7b4341ae2cf3612720)
+on December 28, 2023.
 </em></small>
 
 
@@ -1011,7 +1011,7 @@ All definitions that follow are the score between nodes $u$ and $v$.
 | Resource allocation index | $\sum_{w \in k(u) \cap k(v)} \frac{1}{|k(w)|}$ | [@doi:10.1140/epjb/e2009-00335-8] |
 | Adamic/Adar index | $\sum_{w \in k(u) \cap k(v)} \frac{1}{log|k(w)|}$ | [@doi:10/br5zd3] |
 | Random walk with restart score | $c \bigg[ \bigg( \mathbb{I} - (1-c) \mathbf{A}\bigg)^{-1} \mathbf{y}_u \bigg]_v$ | [@doi:10.1145/1014052.1014135;@raw:laplacian] |
-| Inference score | $\frac{|A(u) \cap D(v)|}{|A(u)|} + \frac{|D(u) \cap D(v)|}{|D(u)|}$ | [@raw:inference] |
+| Inference score | $\frac{|A(u) \cap D(v)|}{|A(u)|} + \frac{|D(u) \cap D(v)|}{|D(u)|}$ | [@doi:10.5821/dissertation-2117-95691] |
 
 Table: Edge prediction features. {#tbl:edge-prediction}
 

references.json

@@ -1985,6 +1985,36 @@
     "URL": "https://doi.org/gs9sq5",
     "note": "This CSL Item was generated by Manubot v0.5.5 from its persistent identifier (standard_id).\nstandard_id: doi:10.5524/102479\nLoaded from an external bibliography file by Manubot.\nsource_bibliography: manual-references-2023-12-21.yaml\noriginal_id: 61xTp8tx"
   },
+  {
+    "type": "thesis",
+    "DOI": "10.5821/dissertation-2117-95691",
+    "id": "yCdaxPuq",
+    "title": "Link prediction in large directed graphs",
+    "publisher": "Universitat Politècnica de Catalunya",
+    "author": [
+      {
+        "given": "Dario",
+        "family": "Garcia Gasulla"
+      }
+    ],
+    "editor": [
+      {
+        "given": "Claudio Ulises",
+        "family": "Cortés García"
+      }
+    ],
+    "issued": {
+      "date-parts": [
+        [
+          2003,
+          12,
+          9
+        ]
+      ]
+    },
+    "URL": "https://doi.org/gtbgzd",
+    "note": "Loaded from an external bibliography file by Manubot.\nsource_bibliography: manual-references.yaml\noriginal_id: yCdaxPuq\nstandard_id: doi:10.5821/dissertation-2117-95691"
+  },
   {
     "publisher": "eLife Sciences Publications, Ltd",
     "abstract": "<jats:p>The ability to computationally predict whether a compound treats a disease would improve the economy and success rate of drug approval. This study describes Project Rephetio to systematically model drug efficacy based on 755 existing treatments. First, we constructed Hetionet (neo4j.het.io), an integrative network encoding knowledge from millions of biomedical studies. Hetionet v1.0 consists of 47,031 nodes of 11 types and 2,250,197 relationships of 24 types. Data were integrated from 29 public resources to connect compounds, diseases, genes, anatomies, pathways, biological processes, molecular functions, cellular components, pharmacologic classes, side effects, and symptoms. Next, we identified network patterns that distinguish treatments from non-treatments. Then, we predicted the probability of treatment for 209,168 compound–disease pairs (het.io/repurpose). Our predictions validated on two external sets of treatment and provided pharmacological insights on epilepsy, suggesting they will help prioritize drug repurposing candidates. This study was entirely open and received realtime feedback from 40 community members.</jats:p>",
@@ -2083,29 +2113,6 @@
     "id": "iPnRRJya",
     "note": "This CSL Item was generated by Manubot v0.5.3 from its persistent identifier (standard_id).\nstandard_id: doi:10.7554/elife.45133\nLoaded from an external bibliography file by Manubot.\nsource_bibliography: manual-references-2023-12-21.yaml\noriginal_id: iPnRRJya"
   },
-  {
-    "type": "thesis",
-    "title": "Link prediction in large directed graphs",
-    "URL": "https://upcommons.upc.edu/handle/2117/95691",
-    "publisher": "Universitat Politècnica de Catalunya",
-    "issued": {
-      "date-parts": [
-        [
-          2015,
-          4,
-          23
-        ]
-      ]
-    },
-    "author": [
-      {
-        "given": "Dario",
-        "family": "Garcia Gasulla"
-      }
-    ],
-    "note": "Loaded from an external bibliography file by Manubot.\nsource_bibliography: manual-references.yaml\nstandard_id: raw:inference",
-    "id": "1EgqwD4S1"
-  },
   {
     "type": "article",
     "URL": "https://dl.acm.org/doi/10.5555/2981345.2981386",
@@ -2142,6 +2149,7 @@
         "family": "Scholkopf"
       }
     ],
+    "page": "321-328",
     "note": "Loaded from an external bibliography file by Manubot.\nsource_bibliography: manual-references.yaml\nstandard_id: raw:laplacian",
     "id": "1E6tdJtDz"
   }

spelling-errors.txt

@@ -5,7 +5,7 @@ AlD
 algo
 algodiagram
 antiparallel
-AUROC
+auroc
 Barabási
 bioinformatics
 bioRxiv
@@ -44,7 +44,7 @@ GpMF
 GpPW
 GuG
 Hanhijärvi
-hetionet
+Hetionet
 Himmelstein
 IndeCut
 Jaccard
@@ -76,7 +76,7 @@ Rxivist
 SCR
 Spearman
 subnetworks
-Subsampled
+subsampled
 TF
 TG
 Translational