Project acronym IP4EC
Project Image processing for enhanced cinematography
Researcher (PI) Marcelo Bertalmío Barate
Host Institution (HI) UNIVERSIDAD POMPEU FABRA
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary The objective is to develop image processing algorithms for cinema that allow people watching a movie on a screen to see the same details and colors as people at the shooting location can. It is due to camera and display limitations that the shooting location and the images on the screen are perceived very differently.
We want to be able to use common cameras and displays (as opposed to highly expensive hardware systems) and work solely on processing the video so that our perception of the scene and of the images on the screen match, without having to add artifical lights when shooting or to manually correct the colors to adapt to a particular display device.
Given that in terms of sensing capabilities cameras are in most regards better than human photoreceptors, the superiority of human vision over camera systems lies in the better processing which is carried out in the retina and visual cortex. Therefore, rather than working on the hardware, improving lenses and sensors, we will instead use, whenever possible, existing knowledge on visual neuroscience and models on visual perception to develop software methods mimicking neural processes in the human visual system, and apply these methods to images captured with a regular camera.
From a technological standpoint, reaching our goal will be a remarkable achievement which will impact how movies are made (in less time, with less equipment, with smaller crews, with more artistic freedom) but also which movies are made (since good-visual-quality productions will become more affordable.) We also anticipate a considerable technological impact in the realm of consumer video.
From a scientific standpoint, this will imply finding solutions for several challenging open problems in image processing and computer vision, but it also has a strong potential to bring methodological advances to other domains like experimental psychology and visual neuroscience.
Summary
The objective is to develop image processing algorithms for cinema that allow people watching a movie on a screen to see the same details and colors as people at the shooting location can. It is due to camera and display limitations that the shooting location and the images on the screen are perceived very differently.
We want to be able to use common cameras and displays (as opposed to highly expensive hardware systems) and work solely on processing the video so that our perception of the scene and of the images on the screen match, without having to add artifical lights when shooting or to manually correct the colors to adapt to a particular display device.
Given that in terms of sensing capabilities cameras are in most regards better than human photoreceptors, the superiority of human vision over camera systems lies in the better processing which is carried out in the retina and visual cortex. Therefore, rather than working on the hardware, improving lenses and sensors, we will instead use, whenever possible, existing knowledge on visual neuroscience and models on visual perception to develop software methods mimicking neural processes in the human visual system, and apply these methods to images captured with a regular camera.
From a technological standpoint, reaching our goal will be a remarkable achievement which will impact how movies are made (in less time, with less equipment, with smaller crews, with more artistic freedom) but also which movies are made (since good-visual-quality productions will become more affordable.) We also anticipate a considerable technological impact in the realm of consumer video.
From a scientific standpoint, this will imply finding solutions for several challenging open problems in image processing and computer vision, but it also has a strong potential to bring methodological advances to other domains like experimental psychology and visual neuroscience.
Max ERC Funding
1 499 160 €
Duration
Start date: 2012-10-01, End date: 2018-03-31
Project acronym NONCODEVOL
Project Evolutionary genomics of long, non-coding RNAs
Researcher (PI) Juan Antonio Gabaldón Estevan
Host Institution (HI) FUNDACIO CENTRE DE REGULACIO GENOMICA
Call Details Starting Grant (StG), LS2, ERC-2012-StG_20111109
Summary Recent genomics analyses have facilitated the discovery of a novel major class of stable transcripts, now called long non-coding RNAs (lncRNAs). A growing number of analyses have implicated lncRNAs in the regulation of gene expression, dosage compensation and imprinting, and there is increasing evidence suggesting the involvement of lncRNAs in various diseases such as cancer. Despite recent advances, however, the role of the large majority of lncRNAs remains unknown and there is current debate on what fraction of lncRNAs may just represent transcriptional noise. Moreover, despite a growing number of lncRNAs catalogues for diverse model species, we lack a proper understanding of how these molecules evolve across genomes. Evolutionary analyses of protein-coding genes have proved tremendously useful in elucidating functional relationships and in understanding how the processes in which they are involved are shaped during evolution. Similar insights may be expected from a proper evolutionary characterization of lncRNAs, although the lack of proper tools and basic knowledge of underlying evolutionary mechanisms are a sizable challenge. Here, I propose to combine state-of-the-art computational and sequencing techniques in order to elucidate what evolutionary mechanisms are shaping this enigmatic component of eukaryotic genomes.The first goal is to enable large-scale phylogenomic analyses of lncRNAs by developing, for these molecules, methodologies that are now standard in the evolutionary analysis of protein-coding genes. The second goal is to explore, at high levels of resolution, the evolutionary dynamics of lncRNAs across selected eukaryotic groups for which novel genome-wide data will be produced experimentally using recently developed sequencing techniques that enable obtaining genome-wide footprints of RNA secondary structure. Finally, this dataset will be used to test the impact on lncRNAs evolution of processes known to be important in protein-coding genes.
Summary
Recent genomics analyses have facilitated the discovery of a novel major class of stable transcripts, now called long non-coding RNAs (lncRNAs). A growing number of analyses have implicated lncRNAs in the regulation of gene expression, dosage compensation and imprinting, and there is increasing evidence suggesting the involvement of lncRNAs in various diseases such as cancer. Despite recent advances, however, the role of the large majority of lncRNAs remains unknown and there is current debate on what fraction of lncRNAs may just represent transcriptional noise. Moreover, despite a growing number of lncRNAs catalogues for diverse model species, we lack a proper understanding of how these molecules evolve across genomes. Evolutionary analyses of protein-coding genes have proved tremendously useful in elucidating functional relationships and in understanding how the processes in which they are involved are shaped during evolution. Similar insights may be expected from a proper evolutionary characterization of lncRNAs, although the lack of proper tools and basic knowledge of underlying evolutionary mechanisms are a sizable challenge. Here, I propose to combine state-of-the-art computational and sequencing techniques in order to elucidate what evolutionary mechanisms are shaping this enigmatic component of eukaryotic genomes.The first goal is to enable large-scale phylogenomic analyses of lncRNAs by developing, for these molecules, methodologies that are now standard in the evolutionary analysis of protein-coding genes. The second goal is to explore, at high levels of resolution, the evolutionary dynamics of lncRNAs across selected eukaryotic groups for which novel genome-wide data will be produced experimentally using recently developed sequencing techniques that enable obtaining genome-wide footprints of RNA secondary structure. Finally, this dataset will be used to test the impact on lncRNAs evolution of processes known to be important in protein-coding genes.
Max ERC Funding
1 302 113 €
Duration
Start date: 2013-01-01, End date: 2017-12-31
Project acronym PRIMATESVS
Project Identification and characterization of primate structural variation and an assessment of intra-specific patterns of selection and copy-number variation
Researcher (PI) Tomas Marques Bonet
Host Institution (HI) UNIVERSIDAD POMPEU FABRA
Call Details Starting Grant (StG), LS2, ERC-2010-StG_20091118
Summary Structural variation and copy-number variant regions (CNVs) (including segmental duplications) are usually underrepresented in genome analyses but are becoming a prominent feature in understanding the organization of genomes as well as many diseases. Large-scale comparative sequencing projects promised a golden era in the study of human evolution, however, many genome regions, especially these complicated regions, are clearly not solved.
Despite international efforts to characterize thousand of human genomes to understand the extent of structural variants in the human species, primates (our closest relatives) have somehow been forgotten. Yet, they are the ideal set of species to study the evolution of these features from both mechanistic and adaptive points of view. Most genome projects include only one individual as a reference but in order to understand the impact of structural variants in the evolution of every species we need to re-sequence multiple individuals of each species. We can only understand the origins of genomic variants and phenotypical differences among species if we can model variation within species and compare it to a proper perspective with the differences among species.
The object of this proposal is to discover the extent of genome structural polymorphism within the great ape species by generating next-generation sequencing datasets at high coverage from multiple individuals of diverse species and subspecies, characterizing structural variants and validating them experimentally. The results of these analyses will assess the rate of genome variation in primate evolution, characterize regional deletions and copy-number expansions as well as determine the patterns of selection acting upon them and whether the diversity of these segments is consistent with other forms of genetic variation among humans and great apes. In so doing, a fundamental insight will be provided into evolutionary variation of these regions among primates and into the mechanisms of disease-causing rearrangements with multiple repercussions in the understanding of evolution and human disease.
Summary
Structural variation and copy-number variant regions (CNVs) (including segmental duplications) are usually underrepresented in genome analyses but are becoming a prominent feature in understanding the organization of genomes as well as many diseases. Large-scale comparative sequencing projects promised a golden era in the study of human evolution, however, many genome regions, especially these complicated regions, are clearly not solved.
Despite international efforts to characterize thousand of human genomes to understand the extent of structural variants in the human species, primates (our closest relatives) have somehow been forgotten. Yet, they are the ideal set of species to study the evolution of these features from both mechanistic and adaptive points of view. Most genome projects include only one individual as a reference but in order to understand the impact of structural variants in the evolution of every species we need to re-sequence multiple individuals of each species. We can only understand the origins of genomic variants and phenotypical differences among species if we can model variation within species and compare it to a proper perspective with the differences among species.
The object of this proposal is to discover the extent of genome structural polymorphism within the great ape species by generating next-generation sequencing datasets at high coverage from multiple individuals of diverse species and subspecies, characterizing structural variants and validating them experimentally. The results of these analyses will assess the rate of genome variation in primate evolution, characterize regional deletions and copy-number expansions as well as determine the patterns of selection acting upon them and whether the diversity of these segments is consistent with other forms of genetic variation among humans and great apes. In so doing, a fundamental insight will be provided into evolutionary variation of these regions among primates and into the mechanisms of disease-causing rearrangements with multiple repercussions in the understanding of evolution and human disease.
Max ERC Funding
1 599 999 €
Duration
Start date: 2010-12-01, End date: 2014-11-30
Project acronym RIBOMYLOME
Project The Role of Non-coding RNA in Protein Networks and Neurodegenerative Diseases
Researcher (PI) Gian Gaetano Tartaglia
Host Institution (HI) FUNDACIO CENTRE DE REGULACIO GENOMICA
Call Details Starting Grant (StG), LS2, ERC-2012-StG_20111109
Summary "A major portion of the eukaryotic genome is occupied by DNA sequences whose transcripts do not code for proteins. This part of the genome is transcribed in a developmentally regulated manner and in response to external stimuli to produce large numbers of long non-coding RNAs (lncRNAs). From the beginning of transcription through splicing and translation, RNA molecules are associated with numerous RNA binding proteins that regulate their processing, stability, transport and translation. Both coding and non-coding RNAs and their associated binding proteins are involved in numerous cellular pathways. These pathways, which include RNA processing and the regulation of transcription and translation, are critical determinants of neuronal differentiation and plasticity. Alterations in these pathways have been identified to contribute to a wide variety of neurodegenerative diseases. Mutations in two RNA binding proteins involved in RNA splicing, the Tar DNA binding protein of 43kd (TDP-43) and Fused in Sarcoma (FUS), cause amyloid aggregation and are associated with Amyotrophic Lateral Sclerosis (ALS). My main interest is to understand the role played by RNA molecules in protein networks. Characterizing protein-RNA associations is key to unravel the complexity and functionality of mammalian genomes. In this project, I propose to study associations of lncRNAs with proteins involved in i) transcriptional regulation and epigenetics (such as polymerases, transcription factors and chromatin-modifiers) and ii) neurodegenerative diseases (such as Parkinson’s -synuclein, Alzheimer’s disease amyloid protein APP, TDP-43 and FUS). In particular, I will investigate if RNA molecules are involved in regulatory mechanisms that control protein production and prevent formation of toxic aggregates. In a multidisciplinary effort, I aim to discover protein-RNA interactions using advanced computational methods developed in my group and state of the art experimental techniques."
Summary
"A major portion of the eukaryotic genome is occupied by DNA sequences whose transcripts do not code for proteins. This part of the genome is transcribed in a developmentally regulated manner and in response to external stimuli to produce large numbers of long non-coding RNAs (lncRNAs). From the beginning of transcription through splicing and translation, RNA molecules are associated with numerous RNA binding proteins that regulate their processing, stability, transport and translation. Both coding and non-coding RNAs and their associated binding proteins are involved in numerous cellular pathways. These pathways, which include RNA processing and the regulation of transcription and translation, are critical determinants of neuronal differentiation and plasticity. Alterations in these pathways have been identified to contribute to a wide variety of neurodegenerative diseases. Mutations in two RNA binding proteins involved in RNA splicing, the Tar DNA binding protein of 43kd (TDP-43) and Fused in Sarcoma (FUS), cause amyloid aggregation and are associated with Amyotrophic Lateral Sclerosis (ALS). My main interest is to understand the role played by RNA molecules in protein networks. Characterizing protein-RNA associations is key to unravel the complexity and functionality of mammalian genomes. In this project, I propose to study associations of lncRNAs with proteins involved in i) transcriptional regulation and epigenetics (such as polymerases, transcription factors and chromatin-modifiers) and ii) neurodegenerative diseases (such as Parkinson’s -synuclein, Alzheimer’s disease amyloid protein APP, TDP-43 and FUS). In particular, I will investigate if RNA molecules are involved in regulatory mechanisms that control protein production and prevent formation of toxic aggregates. In a multidisciplinary effort, I aim to discover protein-RNA interactions using advanced computational methods developed in my group and state of the art experimental techniques."
Max ERC Funding
1 465 351 €
Duration
Start date: 2013-01-01, End date: 2017-12-31
