Após captura de Maduro, Lula demonstra preocupação com falas de Trump sobre Colômbia e Cuba e critica intervenção dos EUA na Venezuela

Many bacterial immune defenses transmit recognition of phage infection via the generation of diverse cyclic nucleotide second messengers. Phage have evolved to subvert this kind of immunity by sequest...

Assista abaixo ao trailer de mais uma produção inédita e original ICL com a participação do Pastor e Deputado Federal Henrique Vieira.

A modelo Luciana Curtis (47), seu marido, o fotógrafo Henrique Gendre (53), e a filha do casal (14) foram encontrados abalados emocionalmente na manhã desta quinta (28) após serem liberados de sequest...

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

"Fomos sequestrados pelos israelenses. Mas essa não é a verdadeira a história. O que está acontecendo é um genocídio em Gaza e uma campanha de fome massiva" Greta Thunberg relata o episódio do sequest...

Many bacterial immune defenses transmit recognition of phage infection via the generation of diverse cyclic nucleotide second messengers. Phage have evolved to subvert this kind of immunity by sequest...

"Coringa: Delírio a Dois" demonstra profundo desprezo por seu público. É uma atitude deliberada e também uma correção de curso empreendida pelo diretor Todd Phillips. Em 2019, ele viu sua obra sequest...

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.