Apply the modifications mentioned by the tutors

assets/abstract.yaml

@@ -2,3 +2,4 @@ spanish-abstract: "Las nuevas técnicas de secuenciación de ADN (NGS) han revol
 spanish-keywords: "deep learning, corrección de errores, receptor de linfocitos T, secuenciación de ADN, inmunología"
 english-abstract: "Next generation sequencing (NGS) techniques have revolutionised genomic research. These technologies perform sequencing of millions of fragments of DNA in parallel, which are pieced together using bioinformatics analyses. Although these techniques are commonly applied, they have non-negligible error rates that are detrimental to the analysis of regions with a high degree of polimorphism. In this study we propose a novel computational method, locimend, based on a Deep Learning algorithm for DNA sequencing error correction. It is applied to the analysis of the complementarity determining region 3 (CDR3) of the T-cell receptor (TCR), generated in silico and subsequently subjected to a sequencing simulator in order to produce sequencing errors. Using these data, we trained a convolutional neural network (CNN) with the aim of generating a computational model that allows the detection and correction of sequencing errors."
 english-keywords: "deep learning, error correction, DNA sequencing, T-cell receptor, immunology"
+acknowdledgments: ""

assets/babathesis.latex

@@ -470,8 +470,7 @@
 
   \textbf{Autor}\\ {$author$}\\[2.5ex]
   \textbf{Directores}\\
-  {Carlos Cano Gutiérrez}\\
-  {María Soledad Benítez Cantos}\\[2cm]
+  {Carlos Cano Gutiérrez}\\[2cm]
   \includegraphics[width=0.3\textwidth]{assets/logo-ceuta.jpg}\\[0.1cm]
   \textsc{Facultad de Educación, Tecnología y Economía de Ceuta}\\
   \textsc{---}\\
@@ -492,6 +491,8 @@
         \vspace{0.5cm}
         \textbf{Keywords:} $english-keywords$
       \end{center}
+    \chapter*{Agradecimientos}
+      $acknowledgements$
     \tableofcontents
     \listoftables{}
     \listoffigures{}

assets/bibliography.bib

@@ -772,3 +772,41 @@
   doi             = {10.1038/35042090},
   url             = {https://doi.org/10.1038/35042090}
 }
+
+@article{doi:10.1146/annurev-genom-090413-025358,
+  author          = {Reinert, Knut and Langmead, Ben and Weese, David and Evers,
+                  Dirk J.},
+  title           = {Alignment of Next-Generation Sequencing Reads},
+  journal         = {Annual Review of Genomics and Human Genetics},
+  volume          = 16,
+  number          = 1,
+  pages           = {133-151},
+  year            = 2015,
+  doi             = {10.1146/annurev-genom-090413-025358},
+  note            = {PMID: 25939052},
+  URL             = { https://doi.org/10.1146/annurev-genom-090413-025358 },
+  eprint          = { https://doi.org/10.1146/annurev-genom-090413-025358 }
+,
+  abstract        = { High-throughput DNA sequencing has considerably changed
+                  the possibilities for conducting biomedical research by
+                  measuring billions of short DNA or RNA fragments. A central
+                  computational problem, and for many applications a first step,
+                  consists of determining where the fragments came from in the
+                  original genome. In this article, we review the main
+                  techniques for generating the fragments, the main
+                  applications, and the main algorithmic ideas for computing a
+                  solution to the read alignment problem. In addition, we
+                  describe pitfalls and difficulties connected to determining
+                  the correct positions of reads. }
+}
+
+@book{book:211898,
+  title           = {Mark's Basic Medical Biochemistry A Clinical Approach},
+  author          = {Michael A. Lieberman, Allan Marks},
+  publisher       = {Lippincott Williams & Wilkins},
+  isbn            = {9780781770224,078177022X},
+  year            = 2008,
+  series          = {Point Lippincott Williams & Wilkins},
+  edition         = {Third},
+  pages           = {209, 260},
+}