Eric Ries was born in September 1978. He graduated from Yale University and moved to silicon Valley in the beginning of the millennium. He pioneered the philosophy of Lean Startup, based on his experience with multiple startups, primary being IMVU which he co-founded along with Will Harvey in 2004. Eric Ries originated his Lean Startup philosophy after getting inspired from the Japanese Philosophy of Lean Manufacturing.

The Lean Startup:How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses

Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35-40 mutations per kb in each population. With these mutation densities, we identified an average of 23-24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.

/pdf/uncovering-hidden-variation-in-polyploid-wheat-46ezbmok6n.pdf

Uncovering hidden variation in polyploid wheat.

Beta-Lactamase Database (BLDB) is a comprehensive, manually curated public resource providing up-to-date structural and functional information focused on this superfamily of enzymes with a great impact on antibiotic resistance. All the enzymes reported and characterised in the literature are presented according to the class (A, B, C and D), family and subfamily to which they belong. All three-dimensional structures of β-lactamases present in the Protein Data Bank are also shown. The characterisation of representative mutants and hydrolytic profiles (kinetics) completes the picture and altogether these four elements constitute the essential foundation for a better understanding of the structure-function relationship within this enzymes family. BLDB can be queried using different protein- and nucleotide-based BLAST searches, which represents a key feature of particular importance in the context of the surveillance of the evolution of the antibiotic resistance. BLDB is available online at http://bldb.eu without any registration and supports all modern browsers.

https://hal.archives-ouvertes.fr/hal-02119817/document

Beta-lactamase database (BLDB) – structure and function

Cotton (Gossypium spp.) is the most important fiber and oil crop in the world. With the emergence of huge -omics data sets, it is essential to have an integrated functional genomics database that allows worldwide users to quickly and easily fetch and visualize genomic information. Currently available cotton-related databases have some weakness in integrating multiple kinds of -omics data from multiple Gossypium species. Therefore, it is necessary to establish an integrated functional genomics database for cotton. We developed CottonFGD (Cotton Functional Genomic Database, https://cottonfgd.org
 ), an integrated database that includes genomic sequences, gene structural and functional annotations, genetic marker data, transcriptome data, and population genome resequencing data for all four of the sequenced Gossypium species. It consists of three interconnected modules: search, profile, and analysis. These modules make CottonFGD enable both single gene review and batch analysis with multiple kinds of -omics data and multiple species. CottonFGD also includes additional pages for data statistics, bulk data download, and a detailed user manual. Equipped with specialized functional modules and modernized visualization tools, and populated with multiple kinds of -omics data, CottonFGD provides a quick and easy-to-use data analysis platform for cotton researchers worldwide.

/pdf/cottonfgd-an-integrated-functional-genomics-database-for-2pmy0rl8lw.pdf

CottonFGD: an integrated functional genomics database for cotton

Summary The MMseqs2 desktop and web server app facilitates interactive sequence searches through custom protein sequence and profile databases on personal workstations. By eliminating MMseqs2's runtime overhead, we reduced response times to a few seconds at sensitivities close to BLAST. Availability and implementation The app is easy to install for non-experts. GPLv3-licensed code, pre-built desktop app packages for Windows, MacOS and Linux, Docker images for the web server application and a demo web server are available at https://search.mmseqs.com. Supplementary information Supplementary data are available at Bioinformatics online.

/pdf/mmseqs2-desktop-and-local-web-server-app-for-fast-mvw9fzb0cc.pdf

MMseqs2 desktop and local web server app for fast, interactive sequence searches

The dramatic drop in DNA sequencing costs has created many opportunities for novel biological research. These opportunities largely rest upon the ability to effectively compare newly obtained and previously known sequences. This is commonly done with BLAST, yet using BLAST directly on new datasets requires substantial technical skills or helpful colleagues. Furthermore, graphical interfaces for BLAST are challenging to install and largely mimic underlying computational processes rather than work patterns of researchers. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver (http://sequenceserver.com), a modern graphical user interface for BLAST. Sequenceserver substantially increases the efficiency of researchers working with sequence data. This is due first to innovations at three levels. First, our software can be installed and used on custom datasets extremely rapidly for personal and shared applications. Second, based on analysis of user input and simple algorithms, Sequenceserver reduces the amount of decisions the user must make, provides interactive visual feedback, and prevents common potential errors that would otherwise cause erroneous results. Finally, Sequenceserver provides multiple highly visual and text-based output options that mirror the requirements and work patterns of researchers. Together, these features greatly facilitate BLAST analysis and interpretation and thus substantially enhance researcher productivity.

https://www.biorxiv.org/content/biorxiv/early/2015/11/27/033142.full.pdf

Sequenceserver: a modern graphical user interface for custom BLAST databases

Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.

/pdf/sequenceserver-a-modern-graphical-user-interface-for-custom-1e5tj92bw4.pdf

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases.

28 The dramatic drop in DNA sequencing costs has created many opportunities for novel biological research. These 29 opportunities largely rest upon the ability to effectively compare newly obtained and previously known sequences. 30 This is commonly done with BLAST, yet using BLAST directly on new datasets requires substantial technical skills or 31 helpful colleagues. Furthermore, graphical interfaces for BLAST are challenging to install and largely mimic underlying 32 computational processes rather than work patterns of researchers. 33 We combined a user-centric design philosophy with sustainable software development approaches to create Se34 quenceserver (http://sequenceserver.com), a modern graphical user interface for BLAST. Sequenceserver sub35 stantially increases the efficiency of researchers working with sequence data. This is due to innovations at three 36 levels. First, our software can be installed and used on custom datasets extremely rapidly for personal and shared 37 applications. Second, based on analysis of user input and simple algorithms, Sequenceserver reduces the amount 38 of decisions the user must make, provides interactive visual feedback, and prevents common potential errors that 39 would otherwise cause erroneous results. Finally, Sequenceserver provides multiple highly visual and text-based output 40 options that mirror the requirements and work patterns of researchers. Together, these features greatly facilitate 41 BLAST analysis and interpretation and thus substantially enhance researcher productivity. 42 2 . CC-BY-NC-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/033142 doi: bioRxiv preprint first posted online Nov. 27, 2015;

Wolfgang Rumpf

Papers

Sequenceserver: a modern graphical user interface for custom BLAST databases

Sequenceserver: A Modern Graphical User Interface for Custom BLAST Databases.

Sequenceserver: a modern graphical user interface