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2021
Autores
Carvalho, S; Gomes, EF;
Publicação
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2021
Abstract
Bird species identification is a relevant and time-consuming task for ornithologists and ecologists. With growing amounts of audio annotated data, automatic bird classification using machine learning techniques is an important trend in the scientific community. Analyzing bird behavior and population trends helps detect other organisms in the environment and is an important problem in ecology. Bird populations react quickly to environmental changes, which makes their real time counting and tracking challenging and very useful. A reliable methodology that automatically identifies bird species from audio would therefore be a valuable tool for the experts in different scientific and applicational domains. The goal of this work is to propose a methodology able to identify bird species by its chirp. In this paper we explore deep learning techniques that are being used in this domain, such as Convolutional Neural Networks and Recurrent Neural Networks to classify the data. In deep learning, audio problems are commonly approached by converting them into images using audio feature extraction techniques such as Mel Spectrograms and Mel Frequency Cepstral Coefficients. We propose and test multiple deep learning and feature extraction combinations in order to find the most suitable approach to this problem.
2021
Autores
Baptista, D; Ferreira, PG; Rocha, M;
Publicação
BRIEFINGS IN BIOINFORMATICS
Abstract
Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of paramount importance for precision medicine. Machine learning(ML) algorithms can be trained on high-throughput screening data to develop models that are able to predict the response of cancer cell lines and patients to novel drugs or drug combinations. Deep learning (DL) refers to a distinct class of ML algorithms that have achieved top-level performance in a variety of fields, including drug discovery. These types of models have unique characteristics that may make them more suitable for the complex task of modeling drug response based on both biological and chemical data, but the application of DL to drug response prediction has been unexplored until very recently. The few studies that have been published have shown promising results, and the use of DL for drug response prediction is beginning to attract greater interest from researchers in the field. In this article, we critically review recently published studies that have employed DL methods to predict drug response in cancer cell lines.We also provide a brief description of DL and the main types of architectures that have been used in these studies. Additionally, we present a selection of publicly available drug screening data resources that can be used to develop drug response prediction models. Finally, we also address the limitations of these approaches and provide a discussion on possible paths for further improvement.
2021
Autores
de Goede, OM; Nachun, DC; Ferraro, NM; Gloudemans, MJ; Rao, AS; Smail, C; Eulalio, TY; Aguet, F; Ng, B; Xu, J; Barbeira, AN; Castel, SE; Kim-Hellmuth, S; Park, Y; Scott, AJ; Strober, BJ; Brown, CD; Wen, X; Hall, IM; Battle, A; Lappalainen, T; Im, HK; Ardlie, KG; Mostafavi, S; Quertermous, T; Kirkegaard, K; Montgomery, SB; Anand, S; Gabriel, S; Getz, GA; Graubert, A; Hadley, K; Handsaker, RE; Huang, KH; Li, X; MacArthur, DG; Meier, SR; Nedzel, JL; Nguyen, DT; Segrè, AV; Todres, E; Balliu, B; Bonazzola, R; Brown, A; Conrad, DF; Cotter, DJ; Cox, N; Das, S; Dermitzakis, ET; Einson, J; Engelhardt, BE; Eskin, E; Flynn, ED; Fresard, L; Gamazon, ER; Garrido-Martín, D; Gay, NR; Guigó, R; Hamel, AR; He, Y; Hoffman, PJ; Hormozdiari, F; Hou, L; Jo, B; Kasela, S; Kashin, S; Kellis, M; Kwong, A; Li, X; Liang, Y; Mangul, S; Mohammadi, P; Muñoz-Aguirre, M; Nobel, AB; Oliva, M; Park, Y; Parsana, P; Reverter, F; Rouhana, JM; Sabatti, C; Saha, A; Stephens, M; Stranger, BE; Teran, NA; Viñuela, A; Wang, G; Wright, F; Wucher, V; Zou, Y; Ferreira, PG; Li, G; Melé, M; Yeger-Lotem, E; Bradbury, D; Krubit, T; McLean, JA; Qi, L; Robinson, K; Roche, NV; Smith, AM; Tabor, DE; Undale, A; Bridge, J; Brigham, LE; Foster, BA; Gillard, BM; Hasz, R; Hunter, M; Johns, C; Johnson, M; Karasik, E; Kopen, G; Leinweber, WF; McDonald, A; Moser, MT; Myer, K; Ramsey, KD; Roe, B; Shad, S; Thomas, JA; Walters, G; Washington, M; Wheeler, J; Jewell, SD; Rohrer, DC; Valley, DR; Davis, DA; Mash, DC; Barcus, ME; Branton, PA; Sobin, L; Barker, LK; Gardiner, HM; Mosavel, M; Siminoff, LA; Flicek, P; Haeussler, M; Juettemann, T; Kent, WJ; Lee, CM; Powell, CC; Rosenbloom, KR; Ruffier, M; Sheppard, D; Taylor, K; Trevanion, SJ; Zerbino, DR; Abell, NS; Akey, J; Chen, L; Demanelis, K; Doherty, JA; Feinberg, AP; Hansen, KD; Hickey, PF; Jasmine, F; Jiang, L; Kaul, R; Kibriya, MG; Li, JB; Li, Q; Lin, S; Linder, SE; Pierce, BL; Rizzardi, LF; Skol, AD; Smith, KS; Snyder, M; Stamatoyannopoulos, J; Tang, H; Wang, M; Carithers, LJ; Guan, P; Koester, SE; Little, AR; Moore, HM; Nierras, CR; Rao, AK; Vaught, JB; Volpi, S;
Publicação
Cell
Abstract
Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.
2021
Autores
Zurek, B; Ellwanger, K; Vissers, LELM; Schüle, R; Synofzik, M; Töpf, A; de Voer, RM; Laurie, S; Matalonga, L; Gilissen, C; Ossowski, S; ’t Hoen, PAC; Vitobello, A; Schulze Hentrich, JM; Riess, O; Brunner, HG; Brookes, AJ; Rath, A; Bonne, G; Gumus, G; Verloes, A; Hoogerbrugge, N; Evangelista, T; Harmuth, T; Swertz, M; Spalding, D; Hoischen, A; Beltran, S; Graessner, H; Haack, TB; Zurek, B; Ellwanger, K; Demidov, G; Sturm, M; Kessler, C; Wayand, M; Wilke, C; Traschütz, A; Schöls, L; Hengel, H; Heutink, P; Brunner, H; Scheffer, H; Steyaert, W; Sablauskas, K; de Voer, RM; Kamsteeg, E; van de Warrenburg, B; van Os, N; te Paske, I; Janssen, E; de Boer, E; Steehouwer, M; Yaldiz, B; Kleefstra, T; Veal, C; Gibson, S; Wadsley, M; Mehtarizadeh, M; Riaz, U; Warren, G; Dizjikan, FY; Shorter, T; Straub, V; Bettolo, CM; Specht, S; Clayton Smith, J; Banka, S; Alexander, E; Jackson, A; Faivre, L; Thauvin, C; Vitobello, A; Denommé Pichon, A; Duffourd, Y; Tisserant, E; Bruel, A; Peyron, C; Pélissier, A; Beltran, S; Gut, IG; Laurie, S; Piscia, D; Matalonga, L; Papakonstantinou, A; Bullich, G; Corvo, A; Garcia, C; Fernandez Callejo, M; Hernández, C; Picó, D; Paramonov, I; Lochmüller, H; Gumus, G; Bros Facer, V; Hanauer, M; Olry, A; Lagorce, D; Havrylenko, S; Izem, K; Rigour, F; Stevanin, G; Durr, A; Davoine, C; Guillot Noel, L; Heinzmann, A; Coarelli, G; Allamand, V; Nelson, I; Yaou, RB; Metay, C; Eymard, B; Cohen, E; Atalaia, A; Stojkovic, T; Macek, M; Turnovec, M; Thomasová, D; Kremliková, RP; Franková, V; Havlovicová, M; Kremlik, V; Parkinson, H; Keane, T; Senf, A; Robinson, P; Danis, D; Robert, G; Costa, A; Patch, C; Hanna, M; Houlden, H; Reilly, M; Vandrovcova, J; Muntoni, F; Zaharieva, I; Sarkozy, A; Timmerman, V; Baets, J; Van de Vondel, L; Beijer, D; de Jonghe, P; Nigro, V; Banfi, S; Torella, A; Musacchia, F; Piluso, G; Ferlini, A; Selvatici, R; Rossi, R; Neri, M; Aretz, S; Spier, I; Sommer, AK; Peters, S; Oliveira, C; Pelaez, JG; Matos, AR; José, CS; Ferreira, M; Gullo, I; Fernandes, S; Garrido, L; Ferreira, P; Carneiro, F; Swertz, MA; Johansson, L; van der Velde, JK; van der Vries, G; Neerincx, PB; Roelofs Prins, D; Köhler, S; Metcalfe, A; Verloes, A; Drunat, S; Rooryck, C; Trimouille, A; Castello, R; Morleo, M; Pinelli, M; Varavallo, A; De la Paz, MP; Sánchez, EB; Martín, EL; Delgado, BM; de la Rosa, FJAG; Ciolfi, A; Dallapiccola, B; Pizzi, S; Radio, FC; Tartaglia, M; Renieri, A; Benetti, E; Balicza, P; Molnar, MJ; Maver, A; Peterlin, B; Münchau, A; Lohmann, K; Herzog, R; Pauly, M; Macaya, A; Marcé Grau, A; Osorio, AN; de Benito, DN; Lochmüller, H; Thompson, R; Polavarapu, K; Beeson, D; Cossins, J; Cruz, PMR; Hackman, P; Johari, M; Savarese, M; Udd, B; Horvath, R; Capella, G; Valle, L; Holinski Feder, E; Laner, A; Steinke Lange, V; Schröck, E; Rump, A;
Publicação
EUROPEAN JOURNAL OF HUMAN GENETICS
Abstract
For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient’s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.
2021
Autores
Schüle, R; Timmann, D; Erasmus, CE; Reichbauer, J; Wayand, M; Baets, J; Balicza, P; Chinnery, P; Dürr, A; Haack, T; Hengel, H; Horvath, R; Houlden, H; Kamsteeg, E; Kamsteeg, C; Lohmann, K; Macaya, A; Marcé Grau, A; Maver, A; Molnar, J; Münchau, A; Peterlin, B; Riess, O; Schöls, L; Schüle, R; Stevanin, G; Synofzik, M; Timmerman, V; van de Warrenburg, B; van Os, N; Vandrovcova, J; Wayand, M; Wilke, C; van de Warrenburg, B; Schöls, L; Wilke, C; Bevot, A; Zuchner, S; Beltran, S; Laurie, S; Matalonga, L; Graessner, H; Synofzik, M; Graessner, H; Zurek, B; Ellwanger, K; Ossowski, S; Demidov, G; Sturm, M; Schulze Hentrich, JM; Heutink, P; Brunner, H; Scheffer, H; Hoogerbrugge, N; Hoischen, A; ’t Hoen, PAC; Vissers, LELM; Gilissen, C; Steyaert, W; Sablauskas, K; de Voer, RM; Janssen, E; de Boer, E; Steehouwer, M; Yaldiz, B; Kleefstra, T; Brookes, AJ; Veal, C; Gibson, S; Wadsley, M; Mehtarizadeh, M; Riaz, U; Warren, G; Dizjikan, FY; Shorter, T; Töpf, A; Straub, V; Bettolo, CM; Specht, S; Clayton Smith, J; Banka, S; Alexander, E; Jackson, A; Faivre, L; Thauvin, C; Vitobello, A; Denommé Pichon, A; Duffourd, Y; Tisserant, E; Bruel, A; Peyron, C; Pélissier, A; Beltran, S; Gut, IG; Laurie, S; Piscia, D; Matalonga, L; Papakonstantinou, A; Bullich, G; Corvo, A; Garcia, C; Fernandez Callejo, M; Hernández, C; Picó, D; Paramonov, I; Lochmüller, H; Gumus, G; Bros Facer, V; Rath, A; Hanauer, M; Olry, A; Lagorce, D; Havrylenko, S; Izem, K; Rigour, F; Durr, A; Davoine, C; Guillot Noel, L; Heinzmann, A; Coarelli, G; Bonne, G; Evangelista, T; Allamand, V; Nelson, I; Yaou, RB; Metay, C; Eymard, B; Cohen, E; Atalaia, A; Stojkovic, T; Macek, M; Turnovec, M; Thomasová, D; Kremliková, RP; Franková, V; Havlovicová, M; Kremlik, V; Parkinson, H; Keane, T; Spalding, D; Senf, A; Robinson, P; Danis, D; Robert, G; Costa, A; Patch, C; Hanna, M; Houlden, H; Reilly, M; Vandrovcova, J; Muntoni, F; Zaharieva, I; Sarkozy, A; de Jonghe, P; Nigro, V; Banfi, S; Torella, A; Musacchia, F; Piluso, G; Ferlini, A; Selvatici, R; Rossi, R; Neri, M; Aretz, S; Spier, I; Sommer, AK; Peters, S; Oliveira, C; Pelaez, JG; Matos, AR; José, CS; Ferreira, M; Gullo, I; Fernandes, S; Garrido, L; Ferreira, P; Carneiro, F; Swertz, MA; Johansson, L; van der Velde, JK; van der Vries, G; Neerincx, PB; Roelofs Prins, D; Köhler, S; Metcalfe, A; Verloes, A; Drunat, S; Rooryck, C; Trimouille, A; Castello, R; Morleo, M; Pinelli, M; Varavallo, A; De la Paz, MP; Sánchez, EB; Martín, EL; Delgado, BM; de la Rosa, FJAG; Ciolfi, A; Dallapiccola, B; Pizzi, S; Radio, FC; Tartaglia, M; Renieri, A; Benetti, E; Balicza, P; Molnar, MJ; Maver, A; Peterlin, B; Münchau, A; Lohmann, K; Herzog, R; Pauly, M; Macaya, A; Marcé Grau, A; Osorio, AN; de Benito, DN; Lochmüller, H; Thompson, R; Polavarapu, K; Beeson, D; Cossins, J; Cruz, PMR; Hackman, P; Johari, M; Savarese, M; Udd, B; Horvath, R; Capella, G; Valle, L; Holinski Feder, E; Laner, A; Steinke Lange, V; Schröck, E; Rump, A;
Publicação
EUROPEAN JOURNAL OF HUMAN GENETICS
Abstract
2021
Autores
Schüle, R; Timmann, D; Erasmus, CE; Reichbauer, J; Wayand, M; Baets, J; Balicza, P; Chinnery, P; Dürr, A; Haack, T; Hengel, H; Horvath, R; Houlden, H; Kamsteeg, EJ; Kamsteeg, C; Lohmann, K; Macaya, A; Marcé Grau, A; Maver, A; Molnar, J; Münchau, A; Peterlin, B; Riess, O; Schöls, L; Schüle, R; Stevanin, G; Synofzik, M; Timmerman, V; van de Warrenburg, B; van Os, N; Vandrovcova, J; Wayand, M; Wilke, C; van de Warrenburg, B; Schöls, L; Wilke, C; Bevot, A; Zuchner, S; Beltran, S; Laurie, S; Matalonga, L; Graessner, H; Synofzik, M; Graessner, H; Zurek, B; Ellwanger, K; Ossowski, S; Demidov, G; Sturm, M; Schulze Hentrich, JM; Heutink, P; Brunner, H; Scheffer, H; Hoogerbrugge, N; Hoischen, A; ’t Hoen, PAC; Vissers, LELM; Gilissen, C; Steyaert, W; Sablauskas, K; de Voer, RM; Janssen, E; de Boer, E; Steehouwer, M; Yaldiz, B; Kleefstra, T; Brookes, AJ; Veal, C; Gibson, S; Wadsley, M; Mehtarizadeh, M; Riaz, U; Warren, G; Dizjikan, FY; Shorter, T; Töpf, A; Straub, V; Bettolo, CM; Specht, S; Clayton Smith, J; Banka, S; Alexander, E; Jackson, A; Faivre, L; Thauvin, C; Vitobello, A; Denommé Pichon, AS; Duffourd, Y; Tisserant, E; Bruel, AL; Peyron, C; Pélissier, A; Beltran, S; Gut, IG; Laurie, S; Piscia, D; Matalonga, L; Papakonstantinou, A; Bullich, G; Corvo, A; Garcia, C; Fernandez Callejo, M; Hernández, C; Picó, D; Paramonov, I; Lochmüller, H; Gumus, G; Bros Facer, V; Rath, A; Hanauer, M; Olry, A; Lagorce, D; Havrylenko, S; Izem, K; Rigour, F; Durr, A; Davoine, CS; Guillot Noel, L; Heinzmann, A; Coarelli, G; Bonne, G; Evangelista, T; Allamand, V; Nelson, I; Yaou, RB; Metay, C; Eymard, B; Cohen, E; Atalaia, A; Stojkovic, T; Macek, M; Turnovec, M; Thomasová, D; Kremliková, RP; Franková, V; Havlovicová, M; Kremlik, V; Parkinson, H; Keane, T; Spalding, D; Senf, A; Robinson, P; Danis, D; Robert, G; Costa, A; Patch, C; Hanna, M; Houlden, H; Reilly, M; Vandrovcova, J; Muntoni, F; Zaharieva, I; Sarkozy, A; de Jonghe, P; Nigro, V; Banfi, S; Torella, A; Musacchia, F; Piluso, G; Ferlini, A; Selvatici, R; Rossi, R; Neri, M; Aretz, S; Spier, I; Sommer, AK; Peters, S; Oliveira, C; Pelaez, JG; Matos, AR; José, CS; Ferreira, M; Gullo, I; Fernandes, S; Garrido, L; Ferreira, P; Carneiro, F; Swertz, MA; Johansson, L; van der Velde, JK; van der Vries, G; Neerincx, PB; Roelofs Prins, D; Köhler, S; Metcalfe, A; Verloes, A; Drunat, S; Rooryck, C; Trimouille, A; Castello, R; Morleo, M; Pinelli, M; Varavallo, A; De la Paz, MP; Sánchez, EB; Martín, EL; Delgado, BM; de la Rosa, FJAG; Ciolfi, A; Dallapiccola, B; Pizzi, S; Radio, FC; Tartaglia, M; Renieri, A; Benetti, E; Balicza, P; Molnar, MJ; Maver, A; Peterlin, B; Münchau, A; Lohmann, K; Herzog, R; Pauly, M; Macaya, A; Marcé Grau, A; Osorio, AN; de Benito, DN; Lochmüller, H; Thompson, R; Polavarapu, K; Beeson, D; Cossins, J; Cruz, PMR; Hackman, P; Johari, M; Savarese, M; Udd, B; Horvath, R; Capella, G; Valle, L; Holinski Feder, E; Laner, A; Steinke Lange, V; Schröck, E; Rump, A;
Publicação
European Journal of Human Genetics
Abstract
In the original publication of the article, consortium author lists were missing in the article. © 2021, The Author(s).
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