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1. Application of Information Spectrum Method on Small Molecules and Target Recognition

Author

Sencanski, Milan, Sumonja, Neven, Perovic, Vladimir, Glisic, Sanja, Veljkovic, Nevena, and Veljkovic, Veljko

Subjects
Quantitative Biology - Biomolecules
Abstract

Current methods for investigation of receptor - ligand interactions in drug discovery are based on three-dimensional complementarity of receptor and ligand surfaces, and they include pharmacophore modelling, QSAR, molecular docking etc. Those methods only consider short-range molecular interactions (distances <5A), and not include long-range interactions (distances >5A) which are essential for kinetic of biochemical reactions because they influence the number of productive collisions between interacting molecules. Previously was shown that the electron-ion interaction potential (EIIP) represents the physical property which determines the long-range properties of biological molecules. This molecular descriptor served as a base for development of the informational spectrum method (ISM), a virtual spectroscopy method for investigation of protein-protein interactions. In this paper, we proposed a new approach to treat small molecules as linear entities, allowing study of the small molecule - protein interaction by ISM. We analyzed here 21 sets of KEGG drug-protein interactions and showed that this new approach allows an efficient discrimination between biologically active and inactive ligands, and consistence with AA regions of their binding site on the target protein., Comment: Keywords: ISM method, CIS spectra, small molecules, smiles notation, target-ligand recognition, protein target regions

Published
2019

3. Exploring the Antiviral Potential of Natural Compounds against Influenza: A Combined Computational and Experimental Approach

Author

Perovic, Vladimir, primary, Stevanovic, Kristina, additional, Bukreyeva, Natalya, additional, Paessler, Slobodan, additional, Maruyama, Junki, additional, López-Serrano, Sergi, additional, Darji, Ayub, additional, Sencanski, Milan, additional, Radosevic, Draginja, additional, Berardozzi, Simone, additional, Botta, Bruno, additional, Mori, Mattia, additional, and Glisic, Sanja, additional

Published
2024
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6. An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T, Bankapur, Asma R, D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S, Kahanda, Indika, Verspoor, Karin M, Ben-Hur, Asa, Koo, Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed ME, Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T, Chapman, Samuel, C., Dukka B K., Khan, Ishita K, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E, Hieta, Reija, Legge, Duncan, Lovering, Ruth C, Magrane, Michele, Melidoni, Anna N, Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon-Charles, Das, Sayoni, Dawson, Natalie L, Lee, David, Lees, Jonathan G, Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E, Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E, Pavlidis, Paul, Feng, Shou, Cejuela, Juan M, Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio, del Pozo, Angela, Fernández, José M, Maietta, Paolo, Valencia, Alfonso, Tress, Michael L, Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W, van Dijk, Aalt DJ, Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C, Vencio, Ricardo ZN, Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael JE, Wass, Mark N, Huntley, Rachael P, Martin, Maria J, O'Donovan, Claire, Robinson, Peter N, Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C, Brenner, Steven E, Linial, Michal, Orengo, Christine A, Rost, Burkhard, Greene, Casey S, Mooney, Sean D, Friedberg, Iddo, and Radivojac, Predrag

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations in technology for generating data and the inherently stochastic nature of biomolecular events have led to the discrepancy between the volume of data and the amount of knowledge gleaned from it. A major bottleneck in our ability to understand the molecular underpinnings of life is the assignment of function to biological macromolecules, especially proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, accurately assessing methods for protein function prediction and tracking progress in the field remain challenging. Methodology: We have conducted the second Critical Assessment of Functional Annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. One hundred twenty-six methods from 56 research groups were evaluated for their ability to predict biological functions using the Gene Ontology and gene-disease associations using the Human Phenotype Ontology on a set of 3,681 proteins from 18 species. CAFA2 featured significantly expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis also compared the best methods participating in CAFA1 to those of CAFA2. Conclusions: The top performing methods in CAFA2 outperformed the best methods from CAFA1, demonstrating that computational function prediction is improving. This increased accuracy can be attributed to the combined effect of the growing number of experimental annotations and improved methods for function prediction., Comment: Submitted to Genome Biology

Published
2016
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7. Computational Modeling and Characterization of Peptides Derived from Nanobody Complementary-Determining Region 2 (CDR2) Targeting Active-State Conformation of the β 2 -Adrenergic Receptor (β 2 AR).

Author

Sencanski, Milan, Glisic, Sanja, Kubale, Valentina, Cotman, Marko, Mavri, Janez, and Vrecl, Milka

Subjects
*MOLECULAR docking, *PEPTIDES, *CELL membranes, *BETA adrenoceptors, *AMINO acids, *MOLECULAR dynamics
Abstract

This study assessed the suitability of the complementarity-determining region 2 (CDR2) of the nanobody (Nb) as a template for the derivation of nanobody-derived peptides (NDPs) targeting active-state β2-adrenergic receptor (β2AR) conformation. Sequences of conformationally selective Nbs favoring the agonist-occupied β2AR were initially analyzed by the informational spectrum method (ISM). The derived NDPs in complex with β2AR were subjected to protein–peptide docking, molecular dynamics (MD) simulations, and metadynamics-based free-energy binding calculations. Computational analyses identified a 25-amino-acid-long CDR2-NDP of Nb71, designated P4, which exhibited the following binding free-energy for the formation of the β2AR:P4 complex (ΔG = −6.8 ± 0.8 kcal/mol or a Ki = 16.5 μM at 310 K) and mapped the β2AR:P4 amino acid interaction network. In vitro characterization showed that P4 (i) can cross the plasma membrane, (ii) reduces the maximum isoproterenol-induced cAMP level by approximately 40% and the isoproterenol potency by up to 20-fold at micromolar concentration, (iii) has a very low affinity to interact with unstimulated β2AR in the cAMP assay, and (iv) cannot reduce the efficacy and potency of the isoproterenol-mediated β2AR/β-arrestin-2 interaction in the BRET2-based recruitment assay. In summary, the CDR2-NDP, P4, binds preferentially to agonist-activated β2AR and disrupts Gαs-mediated signaling. [ABSTRACT FROM AUTHOR]

Published
2024
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15. List of Contributors

Author

Agrawala, Paban K., primary, Amaral, Helena, additional, Arya, Geeta, additional, Balekar, Neelam, additional, Barata, Pedro, additional, Barkan, Nezehat Pınar, additional, Basu, Mitra, additional, Bera, Smritilekha, additional, Bermúdez, José M., additional, Bhise, Satish B., additional, Bilensoy, Erem, additional, Blanco-Méndez, José, additional, Chandra, Ramesh, additional, Cid, Alicia G., additional, Clerici, Stefano P., additional, Dalal, Bhavin, additional, Demiralp, Özerk, additional, Dibi, Manar, additional, Erdoğar, Nazlı, additional, Estanqueiro, Marilene, additional, Faria, Alessandra V. de S., additional, Fernández-Ferreiro, Anxo, additional, Fonseca, Emanuella M.B., additional, Foster, Lauren, additional, Glisic, Sanja, additional, González-Barcia, Miguel, additional, Grewal, Jasleen, additional, Gupta, Nidhi, additional, Gurav, Mayuri V., additional, Halder, Carmen V.F., additional, Jain, Upendra K., additional, Jyoti, Kiran, additional, Karahisar Turan, Seçil, additional, Kaur, Gaganjot, additional, Khaitan, Divya, additional, Lin, Melody, additional, Lopes, Carla M., additional, Lu, Yi, additional, Luzardo, Asteria, additional, Madan, Jitender, additional, Mankamna Kumari, R., additional, Matthews, Marissa, additional, Mehta, S.K., additional, Mohammed, Alyazya, additional, Mondal, Dhananjoy, additional, Nagarsenker, Mangal S., additional, Nair, Hema A., additional, Narayana, Divya S., additional, Nimesh, Surendra, additional, Ningaraj, Nagendra S., additional, Ojha, Himanshu, additional, Oliveira, Rita, additional, Otero-Espinar, Francisco J., additional, Özel Demiralp, Fatma Duygu, additional, Ōzkan, Sibel A., additional, Palma, Santiago D., additional, Pandey, Prasoon, additional, Parmar, Ankush, additional, Pathak, Mallika, additional, Qi, Jianping, additional, Quinn, Thomas J., additional, Reddy, Polluru L., additional, Romero, Analía I., additional, Sharma, Deepti, additional, Sharma, Navneet, additional, Sharma, Nikita, additional, Sharma, Shweta, additional, Simonazzi, Analía, additional, Singh Rajawat, Gopal, additional, Sousa Lobo, José Manuel, additional, Uslu, Bengi, additional, Varan, Cem, additional, Varan, Gamze, additional, Vasconcelos, Helena, additional, Veljkovic, Veljko, additional, Villegas, Mercedes, additional, Wu, Wei, additional, Yadav, Hemant K.S., additional, Yildizhan, Hatice, additional, and Yuhan, Brian, additional

Published
2018
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21. In Silico and In Vitro Inhibition of SARS-CoV-2 PL pro with Gramicidin D.

Author

Protić, Sara, Kaličanin, Nevena, Sencanski, Milan, Prodanović, Olivera, Milicevic, Jelena, Perovic, Vladimir, Paessler, Slobodan, Prodanović, Radivoje, and Glisic, Sanja

Subjects
SARS-CoV-2, COVID-19 treatment, DRUG repositioning, SMALL molecules, PEPTIDE drugs, PROTEOLYTIC enzymes
Abstract

Finding an effective drug to prevent or treat COVID-19 is of utmost importance in tcurrent pandemic. Since developing a new treatment takes a significant amount of time, drug repurposing can be an effective option for achieving a rapid response. This study used a combined in silico virtual screening protocol for candidate SARS-CoV-2 PLpro inhibitors. The Drugbank database was searched first, using the Informational Spectrum Method for Small Molecules, followed by molecular docking. Gramicidin D was selected as a peptide drug, showing the best in silico interaction profile with PLpro. After the expression and purification of PLpro, gramicidin D was screened for protease inhibition in vitro and was found to be active against PLpro. The current study's findings are significant because it is critical to identify COVID-19 therapies that are efficient, affordable, and have a favorable safety profile. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Synthesis, In Silico, and In Vitro Evaluation of Anti-Leishmanial Activity of Oxadiazoles and Indolizine Containing Compounds Flagged against Anti-Targets

Author

Stevanovic, Strahinja, primary, Sencanski, Milan, additional, Danel, Mathieu, additional, Menendez, Christophe, additional, Belguedj, Roumaissa, additional, Bouraiou, Abdelmalek, additional, Nikolic, Katarina, additional, Cojean, Sandrine, additional, Loiseau, Philippe, additional, Glisic, Sanja, additional, Baltas, Michel, additional, and García-Sosa, Alfonso, additional

Published
2019
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37. Feature-Based Classification of Amino Acid Substitutions outside Conserved Functional Protein Domains

Author

Gemovic, Branislava, Perovic, Vladimir, Glisic, Sanja, and Veljkovic, Nevena

Subjects
Article Subject, lcsh:Medicine, Biology, lcsh:Technology, DNA-binding protein, General Biochemistry, Genetics and Molecular Biology, DNA Methyltransferase 3A, Dioxygenases, Epigenesis, Genetic, 03 medical and health sciences, 0302 clinical medicine, Phylogenetics, Proto-Oncogene Proteins, Databases, Genetic, Feature (machine learning), Feature based, Humans, Enhancer of Zeste Homolog 2 Protein, Protein Interaction Domains and Motifs, Statistical analysis, DNA (Cytosine-5-)-Methyltransferases, lcsh:Science, 030304 developmental biology, General Environmental Science, chemistry.chemical_classification, Genetics, 0303 health sciences, lcsh:T, Functional protein, lcsh:R, Polycomb Repressive Complex 2, Computational Biology, Proteins, General Medicine, Amino acid, DNA-Binding Proteins, Repressor Proteins, Amino Acid Substitution, ROC Curve, chemistry, 030220 oncology & carcinogenesis, lcsh:Q, Human genome, Algorithms, Research Article
Abstract

There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs) and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. The new algorithm is based on the informational spectrum method (ISM), a feature-based technique, and statistical analysis. Our dataset contained neutral polymorphisms and mutations associated with myeloid malignancies from epigenetic regulators ASXL1, DNMT3A, EZH2, and TET2. PolyPhen-2 and SIFT had significantly lower accuracies in predicting the effects of amino acid substitutions outside CFDs than expected, with especially low sensitivity. On the other hand, only ISM algorithm showed statistically significant classification of these sequences. It outperformed PolyPhen-2 and SIFT by 15% and 13%, respectively. These results suggest that feature-based methods, like ISM, are more suitable for the classification of amino acid substitutions outside CFDs than phylogeny-based tools.

Published
2013

38. Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Yuxiang Jiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D’Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Indika Kahanda, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M. E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Tunca Dogan, Hakala, Kai, Suwisa Kaewphan, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Ching-Tai Chen, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, Dukka BKC, Ishita K. Khan, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Pooya Zakeri, ElShal, Sarah, Léon-Charles Tranchevent, Sayoni Das, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Prajwal Bhat, Nepusz, Tamás, Romero, Alfonso E., Sasidharan, Rajkumar, Haixuan Yang, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Qingtian Gong, Ning, Wei, Yuanpeng Zhou, Weidong Tian, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., Pozo, Angela Del, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Carlo, Stefano Di, Politano, Gianfranco, Savino, Alessandro, Hafeez Ur Rehman, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., Dijk, Aalt D. J. Van, Gemovic, Branislava, Glisic, Sanja, Vladmir Perovic, Veljkovic, Veljko, Veljkovic, Nevena, Danillo C. Almeida-E-Silva, Vencio, Ricardo Z. N., Malvika Sharan, Vogel, Jörg, Lakesh Kansakar, Shanshan Zhang, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J. E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O’Donovan, Claire, Robinson, Peter N., Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, and Radivojac, Predrag

Abstract

A document containing a subset of CAFA2 analyses that are equivalent to those provided about the CAFA1 experiment in the CAFA1 supplement. (PDF 11100 kb)

Published
2016
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43. In vitroAnti-influenza Activity of in silicoRepurposed Candidate Drug Cycrimine

Author

Matejin, Stanislava, Bukreyeva, Natalya, Radosevic, Draginja, Sencanski, Milan, Mantlo, Emily, Veljkovic, Veljko, Glisic, Sanja, and Paessler, Slobodan

Abstract

Background Due to the limitations of current antiviral therapies because of drug resistance and the emergence of new circulating viral strains, novel effective antivirals are urgently needed. Results of the previous drug repurposing by virtual screening of DrugBank revealed the anticholinergic drug cycrimine as a possible inhibitor of the influenza virus infection.Methods In this study we examined the potential antiviral activity of cycrimine in vitro.Results The experimental results showed the anti-influenza activity of cycrimine against two different influenza A subtypes in cell culture.Conclusions The findings of this study suggest cycrimine as a potential therapeutic agent for influenza.

Published
2019
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44. Y-Chromosomal Diversity in Europe Is Clinal and Influenced Primarily by Geography, Rather than by Language

Author

Rosser, Zoe H., Zerjal, Tatiana, Hurles, Matthew E., Adojaan, Maarja, Alavantic, Dragan, Amorim, Antonio, Amos, William, Armenteros, Manuel, Arroyo, Eduardo, Barbujani, Guido, Beckman, Gunhild, Beckman, Lars, Bertranpetit, Jaume, Bosch, Elena, Bradley, Daniel G., Brede, Gaute, Cooper, Gillian, Corte-Real, Helena B. S. M., de Knijff, Peter, Decorte, Ronny, Dubrova, Yuri E., Evgrafov, Oleg, Gilissen, Anja, Glisic, Sanja, Golge, Mukaddes, Hill, Emmeline W., Jeziorowska, Anna, Kalaydjieva, Luba, Kayser, Manfred, Kivisild, Toomas, Kravchenko, Sergey A., Krumina, Astrida, Kucinskas, Vaidutis, Lavinha, Joao, Livshits, Ludmila A., Malaspina, Patrizia, Maria, Syrrou, McElreavey, Ken, Meitinger, Thomas A., Mikelsaar, Aavo-Valdur, Mitchell, R. John, Nafa, Khedoudja, Nicholson, Jayne, Norby, Soren, Pandya, Arpita, Parik, Juri, Patsalis, Philippos C., Pereira, Luisa, Peterlin, Borut, Pielberg, Gerli, Prata, Maria Joao, Previdere, Carlo, Roewer, Lutz, Rootsi, Siiri, Rubinsztein, D. C., Saillard, Juliette, Santos, Fabricio R., Stefanescu, Gheorghe, Sykes, Bryan C., Tolun, Aslihan, Villems, Richard, Tyler-Smith, Chris, and Jobling, Mark A.

Subjects
Human genetics -- Research, Europeans -- Genetic aspects, Biological sciences
Published
2000

45. An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Jiang, Yuxiang, primary, Oron, Tal Ronnen, additional, Clark, Wyatt T., additional, Bankapur, Asma R., additional, D’Andrea, Daniel, additional, Lepore, Rosalba, additional, Funk, Christopher S., additional, Kahanda, Indika, additional, Verspoor, Karin M., additional, Ben-Hur, Asa, additional, Koo, Da Chen Emily, additional, Penfold-Brown, Duncan, additional, Shasha, Dennis, additional, Youngs, Noah, additional, Bonneau, Richard, additional, Lin, Alexandra, additional, Sahraeian, Sayed M. E., additional, Martelli, Pier Luigi, additional, Profiti, Giuseppe, additional, Casadio, Rita, additional, Cao, Renzhi, additional, Zhong, Zhaolong, additional, Cheng, Jianlin, additional, Altenhoff, Adrian, additional, Skunca, Nives, additional, Dessimoz, Christophe, additional, Dogan, Tunca, additional, Hakala, Kai, additional, Kaewphan, Suwisa, additional, Mehryary, Farrokh, additional, Salakoski, Tapio, additional, Ginter, Filip, additional, Fang, Hai, additional, Smithers, Ben, additional, Oates, Matt, additional, Gough, Julian, additional, Törönen, Petri, additional, Koskinen, Patrik, additional, Holm, Liisa, additional, Chen, Ching-Tai, additional, Hsu, Wen-Lian, additional, Bryson, Kevin, additional, Cozzetto, Domenico, additional, Minneci, Federico, additional, Jones, David T., additional, Chapman, Samuel, additional, BKC, Dukka, additional, Khan, Ishita K., additional, Kihara, Daisuke, additional, Ofer, Dan, additional, Rappoport, Nadav, additional, Stern, Amos, additional, Cibrian-Uhalte, Elena, additional, Denny, Paul, additional, Foulger, Rebecca E., additional, Hieta, Reija, additional, Legge, Duncan, additional, Lovering, Ruth C., additional, Magrane, Michele, additional, Melidoni, Anna N., additional, Mutowo-Meullenet, Prudence, additional, Pichler, Klemens, additional, Shypitsyna, Aleksandra, additional, Li, Biao, additional, Zakeri, Pooya, additional, ElShal, Sarah, additional, Tranchevent, Léon-Charles, additional, Das, Sayoni, additional, Dawson, Natalie L., additional, Lee, David, additional, Lees, Jonathan G., additional, Sillitoe, Ian, additional, Bhat, Prajwal, additional, Nepusz, Tamás, additional, Romero, Alfonso E., additional, Sasidharan, Rajkumar, additional, Yang, Haixuan, additional, Paccanaro, Alberto, additional, Gillis, Jesse, additional, Sedeño-Cortés, Adriana E., additional, Pavlidis, Paul, additional, Feng, Shou, additional, Cejuela, Juan M., additional, Goldberg, Tatyana, additional, Hamp, Tobias, additional, Richter, Lothar, additional, Salamov, Asaf, additional, Gabaldon, Toni, additional, Marcet-Houben, Marina, additional, Supek, Fran, additional, Gong, Qingtian, additional, Ning, Wei, additional, Zhou, Yuanpeng, additional, Tian, Weidong, additional, Falda, Marco, additional, Fontana, Paolo, additional, Lavezzo, Enrico, additional, Toppo, Stefano, additional, Ferrari, Carlo, additional, Giollo, Manuel, additional, Piovesan, Damiano, additional, Tosatto, Silvio C.E., additional, del Pozo, Angela, additional, Fernández, José M., additional, Maietta, Paolo, additional, Valencia, Alfonso, additional, Tress, Michael L., additional, Benso, Alfredo, additional, Di Carlo, Stefano, additional, Politano, Gianfranco, additional, Savino, Alessandro, additional, Rehman, Hafeez Ur, additional, Re, Matteo, additional, Mesiti, Marco, additional, Valentini, Giorgio, additional, Bargsten, Joachim W., additional, van Dijk, Aalt D. J., additional, Gemovic, Branislava, additional, Glisic, Sanja, additional, Perovic, Vladmir, additional, Veljkovic, Veljko, additional, Veljkovic, Nevena, additional, Almeida-e-Silva, Danillo C., additional, Vencio, Ricardo Z. N., additional, Sharan, Malvika, additional, Vogel, Jörg, additional, Kansakar, Lakesh, additional, Zhang, Shanshan, additional, Vucetic, Slobodan, additional, Wang, Zheng, additional, Sternberg, Michael J. E., additional, Wass, Mark N., additional, Huntley, Rachael P., additional, Martin, Maria J., additional, O’Donovan, Claire, additional, Robinson, Peter N., additional, Moreau, Yves, additional, Tramontano, Anna, additional, Babbitt, Patricia C., additional, Brenner, Steven E., additional, Linial, Michal, additional, Orengo, Christine A., additional, Rost, Burkhard, additional, Greene, Casey S., additional, Mooney, Sean D., additional, Friedberg, Iddo, additional, and Radivojac, Predrag, additional

Published
2016
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