We are excited to announce the second computational cancer genomics event in SVAI's Collaborative Research Series. This event will focus on papillary renal-cell carcinoma type 1 (p1RCC), in partnership with RareKidneyCancer.org, Salesforce, Google, NIH, and NCBI.
We will invite 150 researchers, engineers and enthusiasts to join us at Salesforce in San Francisco for an intense weekend of exploration in computational biomedicine. Interdisciplinary teams will work to further understand, develop potential interventions and advance the standard of care for p1RCC. In addition to sequencing a patient for this event, we will use genomic datasets for p1RCC through the NIH's Cancer Genome Atlas.
Papillary renal-cell carcinoma, accounts for between 15 to 20% of all kidney cancers. It occurs in the cells lining the small tubules in the kidney that filter waste from the blood and make urine. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist.
- Advance papillary renal-cell carcinoma research.
- Contribute to real, ongoing patient case.
- Create interdisciplinary opportunities for computer scientists and biologists.
- Learn and develop skills in AI/ML, computational biology and cancer genomics.
- Build an open community for collaborative biomedicine discovery.
- SVAI facilitated sequencing for one p1RCC patient (paid for by UCSF Health): RNA and DNA Whole Genome Sequencing for Tumor and Blood samples, sequenced at 90x using a BGISEQ-500. The data will be available as .bam and .vcf files.
- NIH Cancer Genome Atlas (TCGA) for data for Papillary Renal Cell Carcinoma which includes: RNA-Seq gene expression, identifiable germ-line mutations and some clinical information:
- Exploration of disease pathology and current development efforts/ongoing clinical trials
- Identification of genomic characteristics and driver events of p1RCC.
- Ranking somatic mutations of p1RCC.
- Targeting methods for getting constructs into the RCC cells.
- Identifying gene locations where CRISPR or zinc finger can be applied for treatment.
- Identifying off-label therapeutics through mutational homogeneity.
- Orthogonal assessment of mutated alleles by tumour RNA.
- In Silico HLA Typing Using Standard RNA-Seq Sequence Reads.
- Predicting likelihood of mutated peptides binding autologous HLA-A or HLA-B proteins.
- Create a novel drug intervention with DeepChem.
WHY YOU SHOULD COME
- Advanced learning in computational biology and cancer genomics.
- Great mentoring sessions.
- Make new friends.
- Connect with us and our event partners.
- Our first research event was amazing, and this one will be even better.
MASTERS OF CEREMONY
Ben Busby, PhD
Computational Biology Branch, NCBI, NLM, NIH
MC / MENTOR
Ben leads the NIH's efforts to partner with Genomics hackathons. His research interests include generation of clustering algorithms for analysis of large gene families and whole genomes and Phylomic Analysis of Gene Transfer Events. Ben holds a PhD in Biochemistry and Molecular Biology from University of Maryland, Baltimore.
Dr. James Hsieh, MD, PhD
Professor, Washington University in St. Louis
Department of Medicine, Oncology Division, Molecular Oncology, Medical Oncology
Dr. James Hsieh, MD, PhD, one of North America’s foremost Kidney cancer experts, will be providing the keynote address. Dr. Hsieh is a professor at Washington University's School of Medicine. His research spans Kidney cancer metabolomics, Genomics, Epigenetics, Therapeutics, Precision Medicine, drug development and more.
INVITED RESEARCH PRESENTATION
Dr. Alex Feltus
Associate Professor, Clemson University, Bioinformatics
Clemson University has been working on Translating gene-chemical molecular signature interactions between six tumor subtypes, and will present their findings for:
- Identifying TCGA gene expression signatures that are common and unique between Kidney Chromophobe (KICH), Kidney Renal Clear Cell Carcinoma (KIRC), Kidney Renal Papillary Cell Carcinoma (KIRP), Glioblastoma Multiforme (GBM), and Skin Cutaneous Melanoma (SKCM).
- Molecular signatures that are relevant when sub-grouped into tumor stage or male/female samples.
- Approved drugs or relevant chemicals that interact with PRRC signatures as possible therapeutics.
Bill Paseman has been in Silicon Valley since 1980. He was the Founder and Chairman of Calico Commerce from 1994-2000 and currently focuses on Angel Investing through Paseman & Associates, and advancing rare kidney cancer research and patient advocacy through RareKidneyCancer.org.
Founder, NF2 Project
Onno is the Founder of NF2 Project. He previously founded several other startup companies (such as Tapstack), and now focuses full time on NF2 Project, a patient organization research and treatment options for Neurofibromatosis type 2. He will talk about his experience from the first SVAI research event. Onno has engaged in a life long pursuit of creating things and solving problems. He studied architecture, receiving his degree in 2006 ( honors).
Peter has done a lot of work building healthcare and technology communities in Minnesota and the SF Bay Area. His academic background is Chinese Language and Literature.
Stanford, UC Berkeley, DeepChem Author
Bharath Ramsundar received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He is currently a PhD student in computer science at Stanford University with the Pande group. His research focuses on the application of deep-learning to drug-discovery. In particular, Bharath is the creator and lead-developer of DeepChem, an open source package that aims to democratize the use of deep-learning in drug-discovery and quantum chemistry. He is supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences.
Google Cloud AI
"My current interests are primarily in deep learning for computer vision, image search, and visual similarity search. I am also particularly interested - both from a research perspective as well as a productization perspective - in intelligent systems that allow users to express search intentions or information-needs in nuanced ways that are otherwise difficult to express by language or classical search tools." Clay complted his graduate studies at Stanford University with a dual focus in Human-Computer Interaction and Artificial Intelligence. Prior to joining Google, he worked on Computer Vision and Machine Learning Team at Yahoo on many topics, including scaling deep learning and computer vision technologies for Yahoo products, product integrations, large-scale approximate nearest neighbor search, deep learning for visual similarity search, and visualization tools.
Keren is a Director at SVAI and Machine Learning Engineer at Sift Science, working with distributed machine learning algorithms and delivering real-time solutions to internet-fraud. She was part of the Interactive Robotics Group at MIT CSAIL where she worked to improve machine's ability to extract hierarchical structures from demonstrations of human team collaboration tasks. She graduated from MIT with degrees in Mathematics and EECS. She has also worked at Bloomberg, on distributed systems.
This event was organized by the SVAI Team. Feel free to reach out to any of us.
Avanti is a Ph.D student in the Department of Computer Science at Stanford, advised by Professor Anshul Kundaje. She has develop broadly-applicable methods to make deep learning models interpretable, and has applied these methods to study regulatory genomics. Avanti has a Bachelor's in Computer Science with Molecular Biology from MIT and spent a year working as a developer for the Healthcare team of Palantir Technologies before starting her PhD. Read more at Avanti's Stanford page.
Ankita specializes in studying Epigenetic mechanisms that regulate stem and progenitor cell differentiation during development. She has extensive experience in studying various vertebrate organisms including zebrafish and mice to study in vivo developmental processes, using imaging & genetic strategies. She is enthusiastic about entrepreneurship, and has designed a mentoring program serving Hopkins fellows considering careers in entrepreneurship / start-ups and venture capital strategists. She also serves on the board of Innovation Factory at JHU Carey School of Business to facilitate team building and peer mentoring between business school and science students interested in Entrepreneurship.
We will be issuing Google Cloud credits at the event. Each team will have a provisioned account setup with Google Cloud credits.
We encourage you to use our slack channel and try to get an idea of who you want to work with during the event. The faster teams are formed, the more progress your team will make.
We're creating a few slack channels for easy communication during the event.
We'll introduce our mentors at the beginning of the event. When you have questions, reach out to them! They will around the event and you can reach them on slack as well.
The official event hashtag is: #SolveP1RCC.
We will use Twitter for live announcements and updates from the event. Follow us at @SVAIresearch.
Join our FaceBook Group and share some photos of the event (In-person and remote). Our plan is to periodically live streaming short interviews and broadcasting what people are working on through Facebook. SVAI Facebook.
All the talks from this event will be recorded and made available on SVAI's Youtube Page.
We'd like to see submissions follow the same format as an (abbreviated) academic poster. Submissions are not restricted to this format and we encourage you to be as creative as you want. Push to Github.
- Methods / Algorithms / Models.
- Results and Discussion.
Each team or individual will have 5 Minutes to present what they worked on. Presentations will be fast! But don't worry, we will link submissions here afterwards so you can get a closer look at what everyone worked on.
Each presentation will be judged on the following criteria weighted in this order:
- How well does the solution lead to positive outcomes for Rare Kidney Cancer patient treatment?
- How novel is the approach to finding a solution?
- Quality and depth of the problem analysis.
- Team dynamics, diversity, and intersectionality including cross discipline and specialization collaboration.
Weekend Hackathon (Not an overnight event)
This is a technically intensive event, both from a computer science and bio / genomics perspective. Our target audience is Computer Scientists, AI/ML Researchers, Computational Biologists, Genomic Researchers. Students in any of these areas are especially encouraged to apply!
121 Spear St. @Rincon Cafe
San Francisco, California 94105
BART: 0.2 miles from Embarcadero Station.
FOOD & DRINKS
Standard Event Disclosures
We have a pretty thorough FAQ, please check it out here: FAQ.
CODE OF CONDUCT
Our conference is dedicated to providing a harassment-free conference experience for everyone, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, religion (or lack thereof), or technology choices. We do not tolerate harassment of conference participants in any form. Sexual language and imagery is not appropriate for any conference venue, including talks, workshops, parties, Twitter and other online media. Conference participants violating these rules may be sanctioned or expelled from the conference without a refund at the discretion of the conference organizers. For full version, please see: confcodeofconduct.com.
We take photos at our events. Some of these photos will be used on our website. We seek to respect your privacy and ask that if you do not want your photo to appear on SVAI to please email us.
By signing up for this event, you will automatically be added to future SVAI announcements.
We do not make announcements for non-SVAI events or conferences at our gatherings. Distribution of flyers, printed media or other non SVAI related materials is not allowed at our events.
This gathering is limited to 150 people. You MUST be pre-registered to attend. Registration must include your First and Last name, and some of our venues require ID for entry. You do not need to print a paper ticket. We will be checking people in the building lobby. Questions or comments? Tweet to us @SVAIresearch.