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Ontology-Based Methods for Analyzing Life Science Data
Habilitation a` Diriger des Recherches pr´esent´ee par Olivier Dameron Ontology-based methods for analyzing life science data Soutenue publiquement le 11 janvier 2016 devant le jury compos´ede Anita Burgun Professeur, Universit´eRen´eDescartes Paris Examinatrice Marie-Dominique Devignes Charg´eede recherches CNRS, LORIA Nancy Examinatrice Michel Dumontier Associate professor, Stanford University USA Rapporteur Christine Froidevaux Professeur, Universit´eParis Sud Rapporteure Fabien Gandon Directeur de recherches, Inria Sophia-Antipolis Rapporteur Anne Siegel Directrice de recherches CNRS, IRISA Rennes Examinatrice Alexandre Termier Professeur, Universit´ede Rennes 1 Examinateur 2 Contents 1 Introduction 9 1.1 Context ......................................... 10 1.2 Challenges . 11 1.3 Summary of the contributions . 14 1.4 Organization of the manuscript . 18 2 Reasoning based on hierarchies 21 2.1 Principle......................................... 21 2.1.1 RDF for describing data . 21 2.1.2 RDFS for describing types . 24 2.1.3 RDFS entailments . 26 2.1.4 Typical uses of RDFS entailments in life science . 26 2.1.5 Synthesis . 30 2.2 Case study: integrating diseases and pathways . 31 2.2.1 Context . 31 2.2.2 Objective . 32 2.2.3 Linking pathways and diseases using GO, KO and SNOMED-CT . 32 2.2.4 Querying associated diseases and pathways . 33 2.3 Methodology: Web services composition . 39 2.3.1 Context . 39 2.3.2 Objective . 40 2.3.3 Semantic compatibility of services parameters . 40 2.3.4 Algorithm for pairing services parameters . 40 2.4 Application: ontology-based query expansion with GO2PUB . 43 2.4.1 Context . 43 2.4.2 Objective . -
BIOGRAPHICAL SKETCH NAME: Berger
BIOGRAPHICAL SKETCH NAME: Berger, Bonnie eRA COMMONS USER NAME (credential, e.g., agency login): BABERGER POSITION TITLE: Simons Professor of Mathematics and Professor of Electrical Engineering and Computer Science EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, include postdoctoral training and residency training if applicable. Add/delete rows as necessary.) EDUCATION/TRAINING DEGREE Completion (if Date FIELD OF STUDY INSTITUTION AND LOCATION applicable) MM/YYYY Brandeis University, Waltham, MA AB 06/1983 Computer Science Massachusetts Institute of Technology SM 01/1986 Computer Science Massachusetts Institute of Technology Ph.D. 06/1990 Computer Science Massachusetts Institute of Technology Postdoc 06/1992 Applied Mathematics A. Personal Statement Advances in modern biology revolve around automated data collection and sharing of the large resulting datasets. I am considered a pioneer in the area of bringing computer algorithms to the study of biological data, and a founder in this community that I have witnessed grow so profoundly over the last 26 years. I have made major contributions to many areas of computational biology and biomedicine, largely, though not exclusively through algorithmic innovations, as demonstrated by nearly twenty thousand citations to my scientific papers and widely-used software. In recognition of my success, I have just been elected to the National Academy of Sciences and in 2019 received the ISCB Senior Scientist Award, the pinnacle award in computational biology. My research group works on diverse challenges, including Computational Genomics, High-throughput Technology Analysis and Design, Biological Networks, Structural Bioinformatics, Population Genetics and Biomedical Privacy. I spearheaded research on analyzing large and complex biological data sets through topological and machine learning approaches; e.g. -
PREDICTD: Parallel Epigenomics Data Imputation with Cloud-Based Tensor Decomposition
bioRxiv preprint doi: https://doi.org/10.1101/123927; this version posted April 4, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. PREDICTD: PaRallel Epigenomics Data Imputation with Cloud-based Tensor Decomposition Timothy J. Durham Maxwell W. Libbrecht Department of Genome Sciences Department of Genome Sciences University of Washington University of Washington J. Jeffry Howbert Jeff Bilmes Department of Genome Sciences Department of Electrical Engineering University of Washington University of Washington William Stafford Noble Department of Genome Sciences Department of Computer Science and Engineering University of Washington April 4, 2017 Abstract The Encyclopedia of DNA Elements (ENCODE) and the Roadmap Epigenomics Project have produced thousands of data sets mapping the epigenome in hundreds of cell types. How- ever, the number of cell types remains too great to comprehensively map given current time and financial constraints. We present a method, PaRallel Epigenomics Data Imputation with Cloud-based Tensor Decomposition (PREDICTD), to address this issue by computationally im- puting missing experiments in collections of epigenomics experiments. PREDICTD leverages an intuitive and natural model called \tensor decomposition" to impute many experiments si- multaneously. Compared with the current state-of-the-art method, ChromImpute, PREDICTD produces lower overall mean squared error, and combining methods yields further improvement. We show that PREDICTD data can be used to investigate enhancer biology at non-coding human accelerated regions. PREDICTD provides reference imputed data sets and open-source software for investigating new cell types, and demonstrates the utility of tensor decomposition and cloud computing, two technologies increasingly applicable in bioinformatics. -
Led Zeppelin Iii & Iv
Guitar Lead LED ZEPPELIN III & IV Drums Bass (including solos) Guitar Rhythm Guitar 3 Keys Vocals Backup Vocals Percussion/Extra 1 IMMIGRANT SONG (SD) Aidan RJ Dahlia Ben & Isabelle Kelly Acoustic (main part with high Low acoustic 2 FRIENDS (ENC) (CGCGCE) Mack notes) - Giulietta chords - Turner Strings - Ian Eryn Congas - James Synth (riffy chords) - (strummy chords) - (transitions from 3 CELEBRATION DAY (ENC) James Mack Jimmy Turner Slide - Aspen Friends) - ??? Giulietta Eryn SINCE I'VE BEEN LOVING YOU (Both Rhythm guitar 4 schools) Jaden RJ under solo - ??? Organ - ??? Kelly 5 OUT ON THE TILES (SD) Ethan Ben Dahlia Ryan Kelly Acoustic (starts at Electric solo beginning) - Aspen, (starts at 3:30) - Acoustic (starts at 6 GALLOWS POLE (ENC) Jimmy Mack James 1:05) - Turner Mandolin - Ian Eryn Banjo - Giulietta Electric guitar (including solo Acoustic and wahwah Acoustic main - Rhythm - 7 TANGERINE (SD) (First chord is Am) Ethan Aidan parts) - Isabelle Ben Dahlia Kelly Ryan g Electric slide - Acoustic - Aspen, Mandolin - 8 THAT'S THE WAY (ENC) (DGDGBD) RJ Turner Acoustic #2 - Ian Jimmy Giulietta Eryn Tambo - James Claps - Jaden, Acoustic - Shaker -Ethan, 9 BRON-YR-AUR STOMP (SD) (CFCFAC) Aidan Jaden Dahlia Acoustic - Ben Ryan Kelly Castanets - Kelly HATS OF TO YOU (ROY) HARPER Acoustic slide - 10 (CGCEGC) ??? 11 BLACK DOG (ENC) Jimmy Mack Giulietta James Aspen Eryn Giulietta Piano (starts after solo) - 12 ROCK AND ROLL (SD) Ethan Aidan Dahlia Isabelle Rebecca Ryan Tambo - Aidan Acoustic - Mandolin - The Sandy Jimmy, Acoustic Giulietta, Mandolin -
Lior Pachter Genome Informatics 2013 Keynote
Stories from the Supplement Lior Pachter! Department of Mathematics and Molecular & Cell Biology! UC Berkeley! ! November 1, 2013! Genome Informatics, CSHL The Cufflinks supplements • C. Trapnell, B.A. Williams, G. Pertea, A. Mortazavi, G. Kwan, M.J. van Baren, S.L. Salzberg, B.J. Wold and L. Pachter, Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation, Nature Biotechnology 28, (2010), p 511–515. Supplementary Material: 42 pages. • C. Trapnell, D.G. Hendrickson, M. Sauvageau, L. Goff, J.L. Rinn and L. Pachter, Differential analysis of gene regulation at transcript resolution with RNA-seq, Nature Biotechnology, 31 (2012), p 46–53. Supplementary Material: 70 pages. A supplementary arithmetic progression? • C. Trapnell, B.A. Williams, G. Pertea, A. Mortazavi, G. Kwan, M.J. van Baren, S.L. Salzberg, B.J. Wold and L. Pachter, Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation, Nature Biotechnology 28, (2010), p 511–515. Supplementary Material: 42 pages. • C. Trapnell, D.G. Hendrickson, M. Sauvageau, L. Goff, J.L. Rinn and L. Pachter, Differential analysis of gene regulation at transcript resolution with RNA- seq, Nature Biotechnology, 31 (2012), p 46–53. Supplementary Material: 70 pages. • A. Roberts and L. Pachter, Streaming algorithms for fragment assignment, Nature Methods 10 (2013), p 71—73. Supplementary Material: 98 pages? The nature methods manuscript checklist The nature methods manuscript checklist Emperor Joseph II: My dear young man, don't take it too hard. Your work is ingenious. It's quality work. And there are simply too many notes, that's all. -
A Tribute to Led Zeppelin from Hell's Kitchen Liner Notes
Led Blimpie: A Tribute to Led Zeppelin from Hell’s Kitchen Liner Notes Originally begun as a 3 song demo, this project evolved into a full-on research project to discover the recording styles used to capture Zeppelin's original tracks. Sifting through over 3 decades of interviews, finding the gems where Page revealed his approach, the band enrolled in “Zeppelin University” and received their doctorate in “Jimmy Page's Recording Techniques”. The result is their thesis, an album entitled: A Tribute to Led Zeppelin from Hell's Kitchen. The physical CD and digipack are adorned with original Led Blimpie artwork that parodies the iconic Zeppelin imagery. "This was one of the most challenging projects I've ever had as a producer/engineer...think of it; to create an accurate reproduction of Jimmy Page's late 60's/early 70's analog productions using modern recording gear in my small project studio. Hats off to the boys in the band and to everyone involved.. Enjoy!" -Freddie Katz Co-Producer/Engineer Following is a track-by-track telling of how it all came together by Co-Producer and Led Blimpie guitarist, Thor Fields. Black Dog -originally from Led Zeppelin IV The guitar tone on this particular track has a very distinct sound. The left guitar was played live with the band through a Marshall JCM 800 half stack with 4X12's, while the right and middle (overdubbed) guitars went straight into the mic channel of the mixing board and then into two compressors in series. For the Leslie sounds on the solo, we used the Neo Instruments “Ventilator" in stereo (outputting to two amps). -
Modeling and Analysis of RNA-Seq Data: a Review from a Statistical Perspective
Modeling and analysis of RNA-seq data: a review from a statistical perspective Wei Vivian Li 1 and Jingyi Jessica Li 1;2;∗ Abstract Background: Since the invention of next-generation RNA sequencing (RNA-seq) technolo- gies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels (samples, genes, transcripts, and exons) involve multiple statistical and computational questions, some of which remain challenging up to date. Results: We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusion: The development of statistical and computational methods for analyzing RNA- seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statical models and exhibit dif- ferent performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development. 1 Introduction RNA sequencing (RNA-seq) uses the next generation sequencing (NGS) technologies to reveal arXiv:1804.06050v3 [q-bio.GN] 1 May 2018 the presence and quantity of RNA molecules in biological samples. Since its invention, RNA- seq has revolutionized transcriptome analysis in biological research. RNA-seq does not require any prior knowledge on RNA sequences, and its high-throughput manner allows for genome-wide profiling of transcriptome landscapes [1,2]. -
2019 Wdve Memorial Day 500
2019 WDVE MEMORIAL DAY 500 1 ANOTHER BRICK IN THE WALL PINK FLOYD 2 STAIRWAY TO HEAVEN LED ZEPPELIN 3 SWEET CHILD OF MINE GUNS 'N' ROSES 4 FREEBIRD LYNYRD SKYNYRD 5 BOHEMIAN RHAPSODY QUEEN 6 BLACK DOG LED ZEPPELIN 7 SYMPATHY FOR THE DEVIL THE ROLLING STONES 8 HOTEL CALIFORNIA THE EAGLES 9 WON'T GET FOOLED AGAIN THE WHO 10 WELCOME TO THE JUNGLE GUNS 'N' ROSES 11 WE WILL ROCK YOU/WE ARE THE CHAMPIONS QUEEN 12 YOU SHOOK ME ALL NIGHT LONG AC/DC 13 YOU CAN'T ALWAYS GET WHAT YOU WANT THE ROLLING STONES 14 SWEET EMOTION AEROSMITH 15 PARANOID BLACK SABBATH 16 MONEY PINK FLOYD 17 IMMIGRANT SONG LED ZEPPELIN 18 BABA O' REILLY THE WHO 19 TNT AC/DC 20 CRAZY TRAIN OZZY OSBOURNE 21 WHOLE LOTTA LOVE LED ZEPPELIN 22 ANOTHER ONE BITES THE DUST QUEEN 23 WHO ARE YOU THE WHO 24 BACK IN BLACK AC/DC 25 GIMME SHELTER THE ROLLING STONES 26 LAYLA DEREK & THE DOMINOS 27 PAINT IT BLACK THE ROLLING STONES 28 IMAGINE JOHN LENNON 29 ERUPTION/YOU REALLY GOT ME VAN HALEN 30 COMFORTABLY NUMB PINK FLOYD 31 TURN THE PAGE BOB SEGER 32 ROCK N ROLL LED ZEPPELIN 33 YOU GIVE LOVE A BAD NAME BON JOVI 34 RUNNING DOWN A DREAM TOM PETTY & THE HEARTBREAKERS 35 ENTER SANDMAN METALLICA 36 RUNNIN' WITH THE DEVIL VAN HALEN 37 SWEET HOME ALABAMA LYNYRD SKYNYRD 38 I WON'T BACK DOWN TOM PETTY & THE HEARTBREAKERS 39 SATISFACTION THE ROLLING STONES 40 HONKY TONK WOMEN THE ROLLING STONES 41 WISH YOU WERE HERE PINK FLOYD 42 DREAM ON AEROSMITH 43 BROWN SUGAR THE ROLLING STONES 44 RENEGADE STYX 45 PIANO MAN BILLY JOEL 46 D'YER MAKER LED ZEPPELIN 47 SHATTERED THE ROLLING STONES 48 L.A. -
Human and Mouse Gene Structure: Comparative Analysis and Application to Exon Prediction
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Letter Human and Mouse Gene Structure: Comparative Analysis and Application to Exon Prediction Serafim Batzoglou,1,4,7 Lior Pachter,2,7 Jill P. Mesirov,3 Bonnie Berger,1,4,6 and Eric S. Lander3,5,6 1Laboratory for Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 USA; 2Department of Mathematics, University of California Berkeley, Berkeley, California 94720 USA; 3Whitehead Institute for Biomedical Research, Cambridge, Massachusetts 02142 USA; 4Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 USA; 5Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 USA We describe a novel analytical approach to gene recognition based on cross-species comparison. We first undertook a comparison of orthologous genomic loci from human and mouse, studying the extent of similarity in the number, size and sequence of exons and introns. We then developed an approach for recognizing genes within such orthologous regions by first aligning the regions using an iterative global alignment system and then identifying genes based on conservation of exonic features at aligned positions in both species. The alignment and gene recognition are performed by new programs called GLASS and ROSETTA, respectively. ROSETTA performed well at exact identification of coding exons in 117 orthologous pairs tested. A fundamental task in analyzing genomes is to identify by comparison of syntenic human and mouse genomic the genes. This is relatively straightforward for organ- sequences. isms with compact genomes (such as bacteria, yeast, It is well known that cross-species sequence com- flies and worms) because exons tend to be large and the parison can help highlight important functional ele- introns are either non-existent or tend to be short. -
When the Levee Breaks Chords
Music resources from www.traditionalmusic.co.uk When The Levee Breaks chords (for acoustic guitar an oxymoron?) Led Zeppelin 1970 (Kansas Joe McCoy & Memphis Minnie 1929) Arguably, one of the finest recordings ever mixing the blues with heavy metal rock. About the great Mississippi flood of 1927. Very hard to accurately duplicate because of the heavy amount of studio recording, echo harmonica & special effects. E7* = G string 1st fret + A string 2nd fret (2 finger E7 chord) E7** = E chord + B string 3rd fret (4 finger E7 chord) E chord Repeatedly strum E7*/E/E7**/E7* Play around with different combinations for the best effect, deemphasizing the high E string and emphasizing the low E string Capo I E7*/E/E7**/E7* 18x C D E7*/E 4x C D E7*/E 4x E7* E E7** E If it keeps on raining, levee's goin' to break, 2x E7* E E7** E When the levee breaks I'll have no place to stay. E7*/E/E7**/E7* 2x E7* E E7** E Mean old levee taught me to weep and moan, 2x E7* E E7** E Got what it takes to make a mountain man leave his home, E7* E E7* E E7* E Oh, well, oh, well, oh, well. C D E7*/E 4x C D E7*/E 4x E7*/E E7*/B E7* A D E E7* E Don't it make you feel bad B When you're trying to find your way home, A D E You don't know which way to go? E7* E If you're goin' down South B They got no work to do, A D E If you don't know about Chicago. -
Eric S. Lander
Chancellor's Distinguished Fellows Program 2004-2005 Selective Bibliography UC Irvine Libraries Eric S. Lander February 25, 2005 Prepared by: John E. Sisson Biological Sciences Librarian [email protected] Journal Articles (Selected from over 220 articles he has authored or co-authored) Poirier, C., Y. J. Qin, C.P. Adams, Y. Anaya, J. B. Singer, A. E. Hill, Eric S. Lander, J.H. Nadeau, and C. E. Bishop. "A complex interaction of imprinted and maternal-effect genes modifies sex determination in odd sex (Ods) mice." Genetics 168, no. 3 (2004): 1557-1562. Skuse, D. H., S. Purcell, M. J. Daly, R. J. Dolan, J. S. Morris, K. Lawrence, Eric S. Lander, and P. Sklar. "What can studies on Turner syndrome tell us about the role of X- linked genes in social cognition?." American Journal of Medical Genetics Part B- Neuropsychiatric Genetics 130B, no. 1 (2004): 8-9. Rioux, J. D., H. Karinen, K. Kocher, S. G. McMahon, P. Karkkainen, E. Janatuinen, M. Heikkinen, R. Julkunen, J. Pihlajamaki, A. Naukkarinen, V. M. Kosma, M. J. Daly, Eric S. Lander, and M. Laakso. "Genomewide search and association studies in a Finnish celiac disease population: Identification of a novel locus and replication of the HLA and CTLA4 loci." American Journal of Medical Genetics Part A 130A, no. 4 (2004): 345- 350. Michalkiewicz, M., T. Michalkiewicz, R. A. Ettinger, E. A. Rutledge, J. M. Fuller, D. H. Moralejo, B. Van Yserloo, A. J. MacMurray, A. E. Kwitek, H. J. Jacob, Eric S. Lander, and A. Lernmark. "Transgenic rescue demonstrates involvement of the Ian5 gene in T cell development in the rat." Physiological Genomics 19, no. -
Rethinking the Law on Corporate Manslaughter to Better Reflect the Artificial Legal Existence of Corporations
Plymouth Law and Criminal Justice Review (2019) ARE CORPORATIONS FREE TO KILL? RETHINKING THE LAW ON CORPORATE MANSLAUGHTER TO BETTER REFLECT THE ARTIFICIAL LEGAL EXISTENCE OF CORPORATIONS 1 Lucy Hooper Abstract This year, 2018, marks the 10 year anniversary of the implementation of the Corporate Manslaughter and Corporate Homicide Act 2007. It is, therefore, an appropriate time to review its effectiveness and consider whether the Act has achieved what it set out to. Its introduction was a parliamentary attempt to address the key defects’2 under the previous identification doctrine, where a company’s liability was dependant on gross negligent manslaughter being sought in the relevant directing mind and will. This article will highlight the inadequacies of the former regime and review to what extent the 2007 Act has resolved them. Importantly, it references the recent Grenfell Tower disaster, which, if corporate manslaughter charges are pursued, will be the Act’s biggest and most public challenge to date. Keywords: corporate manslaughter, Corporate Manslaughter and Corporate Homicide Act 2007, gross negligent manslaughter Introduction Companies, as a result of Salomon3, are ‘distinct and independent’4 entities separate from their members. However, in reality, ‘corporations have no consciences, no beliefs, no feelings, no thoughts, no desires’ and merely ‘help structure and facilitate the activities of human beings’. 5 Consequently, under the original common law models, corporate criminal liability had to be found in individuals and then ‘attributed’ to the company. Attribution in the UK, commonly takes two forms. The first, vicarious liability, imposes liability on corporations ‘for the criminal acts of employees…acting within the scope of their employment’.6 It is, ‘wholly derivative’.7 While the principle is easily applied, ‘a corporation is not…so abstract, impalpable 1 Lucy graduated with a first class LLB honours and was awarded the Womble Bond Dickinson prize for the best student undertaking commercial law.