This covers details of the processes of compilation. A lot of extra teaching support is required with these.
Originally written for AQA A level Computing (UK exam).
Open source general-purpose. Multiplatform programming language
Object Oriented, Procedural, Functional
Easy to interface with C/ObjC/Java/Fortran
Easy to interface with C++ (via SWIG)
Great interactive environment
Python 'philosophy' emphasis readability, clarity and simplicity
The Interactive Interpreter
it is very easy to learn and understand.
Corpus annotation for corpus linguistics (nov2009)Jorge Baptista
Lecture on corpus annotation for corpus linguistics. Contents: DIY corpus, e-texts, character set and text encoding issues, document structure, DTDs, documentation;
tools and issues in annotation procedures, good practices; examples from anaphora resolution and named entity recognition annotation campaigns; evaluation of corpus annotation
Presentation for SSW11: "Preliminary study on using vector quantization latent spaces for TTS/VC systems with consistent performance"
Presenter: Hieu-Thi Luong
Preprint: https://arxiv.org/abs/2106.13479
This covers details of the processes of compilation. A lot of extra teaching support is required with these.
Originally written for AQA A level Computing (UK exam).
Open source general-purpose. Multiplatform programming language
Object Oriented, Procedural, Functional
Easy to interface with C/ObjC/Java/Fortran
Easy to interface with C++ (via SWIG)
Great interactive environment
Python 'philosophy' emphasis readability, clarity and simplicity
The Interactive Interpreter
it is very easy to learn and understand.
Corpus annotation for corpus linguistics (nov2009)Jorge Baptista
Lecture on corpus annotation for corpus linguistics. Contents: DIY corpus, e-texts, character set and text encoding issues, document structure, DTDs, documentation;
tools and issues in annotation procedures, good practices; examples from anaphora resolution and named entity recognition annotation campaigns; evaluation of corpus annotation
Presentation for SSW11: "Preliminary study on using vector quantization latent spaces for TTS/VC systems with consistent performance"
Presenter: Hieu-Thi Luong
Preprint: https://arxiv.org/abs/2106.13479
Language Server Protocol - Why the Hype?mikaelbarbero
The Language Server Protocol developed by Microsoft for Visual Studio Code is a language and IDE agnostic protocol which clearly separates language semantics from UI presentation. Language developers can implement the protocol and benefit from immediate support in all IDEs, while IDE developers, who implement the protocol get automatic support for all these languages without having to write any language-specific code. This session will let you learn more about the innards of the LSP. We will also have an overview of the current implementations in Eclipse, and outside Eclipse as well.
Network Protocol Testing Using Robot FrameworkPayal Jain
The slides describes how Robot Framework provides synergy in test automation, making a lot of
automation processes flexible and simple for testing network protocols(in this case BGP).
Detailed presentation on various analytical tools widely used in Corpus Linguistics for corpora analysis including WORDCRUNCHER, LEXA, CWB , TACT, MICROCONCORD etc.
Similar to BEL.bio Overview and BioDati Studio (20)
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
2. Why BEL?
Chemists have the Chemical Reaction Language
Biologists have the Biological Expression Language (BEL)
Open standard for communication and knowledge-storage
Whiteboard and Computer friendly
Partial chemical synthesis pathway: https://www.synarchive.com/syn/128
3. Overall Goals for BEL.bio
Try to simplify use of BEL and BEL Content
Stronger BEL/Nanopub validation, better error messages
Easy addition of new BEL Language features
Convert to Python and Docker
Easier community engagement
Quick easy startup/deployment
Provide API and Namespaces hosting
Easier to use/deploy/maintain search/completion service
Greatly expand organisms supported (all EntrezGene/NCBITaxonomy)
Simplify addition/maintenance of namespaces/zero downtime updates!!!
4. Glossary
BEL Assertion – single string version of BEL or subject, relation, object
(SRO) version of BEL assertion (e.g. BEL triple)
BEL Nanopub – BEL triple, Evidence, Context, Citation, Metadata
Evidence – short text extraction or supporting information for BELTriple (Evidence
in BEL Script, Support in OpenBEL Nanopub format)
Annotations – OpenBEL Annotations are now called Annotations and were referred
to as Experimental Context in BELMgr
BEL Edge – BEL triples, primary and computed BEL canonicalized to
standard namespace IDs and potentially orthologized stored in the
EdgeStore (a graph database)
API – BEL.bio API – BEL language, nanopub, terminology (namespace,
orthology) services
AST – Abstract SyntaxTree of BEL Statement
Function: BEL function, e.g. p() or modifier function, e.g. var()
NSArg: Namespace argument, e.g. HGNC:AKT1
StrArg: String argument, e.g. pmod(Ph,T, 22), Ph,T and 22 are string arguments
5. Not supported by BEL.bio
KAMs
OpenBEL API/tooling
BELScripts (except for converting to BEL Nanopubs)
XBEL
OpenBEL namespace/equivalence files (limited conversion to
BEL.bioTerminology files)
6. BEL Parsing and Validation
bel_lang python module
Depends on BEL.bio API for terminology services (namespaces, equivalents,
orthology)
Parsing, validation, canonicalization, orthologization, compute
edges (eventually completion and migration)
Uses BEL Specification and EBNF file for parsing and semantic
validation
EBNF file used byTatsu module to create parser library to parse BELTriple
into dictionary AST of Function, NSArg, StrArg components,AST is
transformed to python AST class-based object (BEL Object BO)
BEL Spec used to process BO for semantic validation
bo.parse('p(MGI:A1bg)').orthologize('TAX:9606').canonicalize().ast.to_string(fmt='medium')
p(EG:1)
Provides CLI installed with module
7. Supports Multiple BEL versions
Can deploy bel_lang with multiple BEL versions (only BEL 2.0.0
currently (using semantic versioning now for BEL)
One BEL Specification file per version, EBNF/parser generated from
BEL Spec
Drop in new BEL Spec, get new BELVersion functionality, easy
testing of proposed BEL language features
Future: create BEL migration signatures like the computed edge
signatures for migrating BEL
14. BEL Terminology Resources
Simplify Namespaces
GOBP, GOCC, GOBPID, GOCCID -> GO
Context (Annotations) are now also Namespaces
Simplify generator scripts
Single script per resource: download and reformat into
terminology or orthology load file
Single download/cache directory (gzipped)
BEL Resource tools Github repo
https://github.com/belbio/bel_resources
22. location: 1501 Main Street, Rahway, NJ 07065 | call: 732-764-8844 | online: biodati.com
Anselmo Di Fabio
adifabio@biodati.com
William Hayes
whayes@biodati.com
Editor's Notes
History of BEL – developed over 10 years ago by Dexter Pratt at Genstruct (renamed to Selventa) and used for biomarker development as well as drug and toxicology mechanism analysis. BEL was was open-sourced about 5 years ago by Selventa by David de Graaf.