2024 · paper
Characterization of Alternative Splicing in High-Risk Wilms’ Tumors
Characterizes alternative-splicing patterns in the studied high-risk Wilms tumor material.[70]
Single-cell genomics and tissue regeneration
Tomer Kalisky
תומר קליסקי
Identity: verifiedThe BIU profile uses Tomer Kalisky and matches the roster; the patent record independently lists the same name. [70]
Documented foundation
Research & experience
Kalisky applies single-cell genomics to stem cells, regeneration, cancer, and tissue-state characterization.[70]
single-cell expression profilingstem-cell biologycancer genomicscell-state inference
CV and official profile
The BIU profile and its career information were inspected; no standalone current CV was verified.[70]
Selected work
Representative records, not a complete publication list. Metadata confirms attribution; it does not independently replicate a result.
Patent evidence
2 catalogued patent records · 1 identified family · family unassigned for 1 record
Coverage: Partial inventor search
Added Stanford Methods and systems for analysis of single cells family, corroborated by the researcher's own patent list. Baseline Single cell gene expression family retained without duplicate grants. Same-name fingerprint-device candidates US20180260603A1 and US20180253588A1 surfaced in an index search but were not attributed: no identity bridge and no individual inspection within this pass.
Methods and systems for analysis of single cells
US9850483B2 · Published 2017-12-26
Published patent document inspected
Publication assignee: Leland Stanford Junior University
Named inventor Tomer Kalisky; own institutional patent list corroborates application/title/co-inventor identity. Assignee is the captured publication metadata, not a current-ownership determination.[238][249]
Single cell gene expression for diagnosis, prognosis and identification of drug targets
US20160312302A1
Original report record
Preserved from the original report; see its cited evidence and limitations.[71]
Original report snapshot
Original evidence: verified record
The record verifies inventor attribution to this publication family; legal status and current ownership are not treated as research conclusions.[71]
Records are counted separately from identified families. Author-reported entries are labelled and may still need publication verification. Inventorship, publication-time applicant and current ownership are different facts. No legal-status, patentability or freedom-to-operate conclusion is made.
Scores prioritize research fit from 1–10; they are not probabilities.
Review: Reviewed with limitations
Proposed capability matches, not confirmed relationships. Scores are analyst judgments with low forecast confidence; researcher interests, capacity and feasibility need confirmation.
Internal connections
13 candidates
Connection 1
Orr Levy
Original proposal
Proposal hypothesis: Levy's multi-omics network models and Kalisky's cell-state biology meet on whether ageing-associated failure signals survive cell-composition adjustment.[5][6][70]
First test and score details
First test
Proposed first test: Reanalyse one open single-cell ageing dataset with cell-type stratification; test held-out state discrimination against composition-only baselines.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 4
Why this rank
Rank 1/13; fit 10/10 (4 topic overlap + 3 complementarity + 3 feasible first test). Preserved original co-membership proposal in o04. No strictly higher-scoring candidate displaces this original. The test is computationally bounded; predictive associations do not establish an ageing mechanism. No automatic score boost for original membership. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 2
Jacob Goldberger
Proposal hypothesis: Kalisky's single-cell state questions and Goldberger's statistical learning support uncertainty-aware cell-state classification.[70][75][76]
First test and score details
First test
Proposed first test: Hold out one public single-cell study and compare calibrated and uncalibrated state assignments on rare-cell recall and rejection rate.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 4
Why this rank
Rank 2/13; fit 10/10 (4 topic overlap + 3 complementarity + 3 feasible first test). New pairing outside the frozen portfolio co-member graph. No clinical interpretation or mechanistic inference follows from classification accuracy alone. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 3
Shahar Alon
Original proposal
Proposal hypothesis: Alon's spatial transcriptomics and Kalisky's single-cell state analysis can distinguish true tissue-state structure from dissociation or spatial measurement artifacts.[60][61][70]
First test and score details
First test
Proposed first test: Compare cell-state assignments from matched public spatial and single-cell data, with coordinate-shuffle and expression-depth controls.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 4
Why this rank
Rank 3/13; fit 9/10 (4 topic overlap + 3 complementarity + 2 feasible first test). Preserved original co-membership proposal in o04. An added candidate, Jacob Goldberger (10/10), ranks above this original because its stated pair-specific roles and first test score higher; this original is limited as follows: The strongest shared biological question still depends on an appropriate matched dataset and a tissue-specific interpretation protocol. No automatic score boost for original membership. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Show 10 moreShow fewer internal connections
Connection 4
Leonid Yavits
Original proposal
Proposal hypothesis: Kalisky can specify which cell-state distinctions must survive while Yavits changes the architecture executing a genomic classifier.[70][104][105]
First test and score details
First test
Proposed first test: Run an exact and approximate kernel on a public labelled single-cell dataset and compare rare-state retention alongside latency and memory traffic.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 3
Why this rank
Rank 4/13; fit 9/10 (3 topic overlap + 3 complementarity + 3 feasible first test). Preserved original co-membership proposal in o02. An added candidate, Jacob Goldberger (10/10), ranks above this original because its stated pair-specific roles and first test score higher; this original is limited as follows: The selected single-cell task must actually map to the accelerator; pathogen-kernel performance cannot be transferred automatically. No automatic score boost for original membership. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 5
Yoli Shavit
Original proposal
Proposal hypothesis: Kalisky contributes single-cell state interpretation while Shavit's announced complex-data programme motivates uncertainty-aware transfer across biological datasets.[70][127][128]
First test and score details
First test
Proposed first test: Hold out one study in a public single-cell benchmark and compare calibrated state prediction with nearest-neighbour and cell-composition baselines.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 3
Why this rank
Rank 5/13; fit 9/10 (3 topic overlap + 3 complementarity + 3 feasible first test). Preserved original co-membership proposal in o02, o04. An added candidate, Jacob Goldberger (10/10), ranks above this original because its stated pair-specific roles and first test score higher; this original is limited as follows: Biological direction is an announced research interest for Shavit; current laboratory operation and biological results are unverified. No automatic score boost for original membership. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work. Yoli Shavit biological/multimodal programme evidence is a 2025 announcement; current laboratory operation and biological experimental capability are not established. Original initiative conditions remain: o02 Yoli Shavit: Conditional later role: test uncertainty and generalization only after a specific cross-domain fidelity question is preregistered.
Connection 6
Orit Shefi
Proposal hypothesis: Shefi can define a regenerative-culture perturbation and Kalisky can distinguish altered cell states from simple shifts in cell abundance.[8][70]
First test and score details
First test
Proposed first test: Specify a small perturbation/control panel and analyse a relevant open single-cell reference for state markers and composition confounding.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 4
Why this rank
Rank 6/13; fit 9/10 (4 topic overlap + 3 complementarity + 2 feasible first test). New pairing outside the frozen portfolio co-member graph. The selected culture model needs biological qualification; predicted state shifts are not nerve repair. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 7
Rachela Popovtzer
Proposal hypothesis: Popovtzer can define nanoparticle targeting controls while Kalisky distinguishes cellular states that may explain heterogeneous uptake.[53][54][70]
First test and score details
First test
Proposed first test: Use a public cell-state dataset to preregister target-positive and target-negative groups for a later blinded uptake assay.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 3
Why this rank
Rank 7/13; fit 8/10 (3 topic overlap + 3 complementarity + 2 feasible first test). New pairing outside the frozen portfolio co-member graph. RNA-defined states do not establish accessible protein targets or therapeutic response. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 8
Adam Teman
Original proposal
Proposal hypothesis: Teman can quantify energy and reduced-precision costs while Kalisky defines biological fidelity for a single-cell analysis pipeline.[1][70]
First test and score details
First test
Proposed first test: Quantize one public cell-state classifier and plot memory-access reduction against rare-cell recall and expression-derived state stability.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 8/13; fit 7/10 (2 topic overlap + 3 complementarity + 2 feasible first test). Preserved original co-membership proposal in o02. An added candidate, Jacob Goldberger (10/10), ranks above this original because its stated pair-specific roles and first test score higher; this original is limited as follows: This cross-field link depends on a chosen computational kernel and biological labels; no wet-lab or chip availability is assumed. No automatic score boost for original membership. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 9
Alex Fish
Original proposal
Proposal hypothesis: Fish can model low-energy biomedical memory hardware while Kalisky can define which cell-state errors invalidate a biological conclusion.[70][89][90]
First test and score details
First test
Proposed first test: Inject bounded memory/readout errors into one open single-cell classifier and measure rare-state recall versus a fault-free reference.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 9/13; fit 7/10 (2 topic overlap + 3 complementarity + 2 feasible first test). Preserved original co-membership proposal in o02. An added candidate, Jacob Goldberger (10/10), ranks above this original because its stated pair-specific roles and first test score higher; this original is limited as follows: The connection is useful only after defining a hardware-sensitive kernel; neither source establishes a ready shared platform. No automatic score boost for original membership. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work. Original initiative conditions remain: o02 Alex Fish: Alternative or later circuit lead: assess memory/circuit precision and energy tradeoffs if the chosen implementation needs this expertise; security is outside the initial test.
Connection 10
Yaara Erez
Proposal hypothesis: Erez can specify a brain-function question while Kalisky's single-cell analysis can identify cellular composition confounds in molecular correlates.[28][29][70]
First test and score details
First test
Proposed first test: Compare brain-region cell-composition features with functional-network descriptors in public aggregate atlases, using spatially matched nulls.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 10/13; fit 7/10 (2 topic overlap + 3 complementarity + 2 feasible first test). New pairing outside the frozen portfolio co-member graph. Cross-atlas association cannot connect a single-cell state directly to cognition. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 11
Amos Danielli
Proposal hypothesis: Kalisky can define a cell-state marker question while Danielli tests whether a portable protein assay reflects the corresponding molecular state.[45][46][47][70]
First test and score details
First test
Proposed first test: On a public matched transcript/protein dataset or a prespecified future panel, compare marker association with a cell-composition baseline.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 11/13; fit 7/10 (2 topic overlap + 3 complementarity + 2 feasible first test). New pairing outside the frozen portfolio co-member graph. Transcript abundance is not protein concentration; matched data must exist before assay claims. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 12
Ori Ernst
Proposal hypothesis: Kalisky can define biologically meaningful cell-state claims and Ernst can test whether summaries preserve their exact supporting evidence and caveats.[70][93][94][95]
First test and score details
First test
Proposed first test: Adjudicate a small open single-cell paper set and compare source-aligned summaries on state-label accuracy and omitted experimental limitations.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 12/13; fit 7/10 (2 topic overlap + 3 complementarity + 2 feasible first test). New pairing outside the frozen portfolio co-member graph. Domain review is essential; source alignment cannot establish the truth of a biological claim. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
Connection 13
Hila Chalutz-Ben Gal
Proposal hypothesis: Kalisky's single-cell workflows provide a scientific task taxonomy for Chalutz-Ben Gal's person-skill fit and AI-adoption research.[22][23][70]
First test and score details
First test
Proposed first test: Draft a workflow/skill map for one public single-cell analysis tutorial and test the rubric for missing handoff responsibilities.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 1
Why this rank
Rank 13/13; fit 6/10 (1 topic overlap + 3 complementarity + 2 feasible first test). New pairing outside the frozen portfolio co-member graph. This is research-workflow and training fit, not biological expertise for Chalutz-Ben Gal or a confirmed team. Equal scores use existing-first, then stable researcher ID.
Conditions
Analyst proposal hypothesis, not an established collaboration, commitment, evidence-confidence rating or assessment of researcher quality; confirm participation and access before work.
External connections
10 candidates
Connection 1
Rahul Satija
New York Genome Center and New York University
Proposed capability match: Tomer Kalisky's single-cell expression profiling, stem-cell biology can be paired with Rahul Satija's documented single-cell genomics, multimodal integration for longitudinal single-cell repair atlas. The specific contribution is single-cell multimodal integration; this transfer is an analyst hypothesis.[70][492]
First test and score details
First test
Compare modality-specific and integrated embeddings with donor-held-out cell-type annotations using a public longitudinal or staged tissue-repair single-cell dataset split by donor and time. Compare label transfer, batch sensitivity and rare-state recovery with a static cell-state classifier without trajectory information.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 4
Why this rank
Rank 1/10 after semantic revision; analyst score 10 = max(1, 4+3+3): topic overlap 4/4, complementarity 3/3, feasible first test 3/3. A bounded offline comparison is specified; required datasets and domain assumptions must still be checked.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified.
Connection 2
Sarah Teichmann
University of Cambridge
Original proposal
Her cell-atlas and tissue-architecture program could complement integration across tissues and spatial validation; no willingness is asserted.[70][72][495]
First test and score details
First test
Collect a small injury-recovery time course and test whether predefined trajectories reproduce across biological replicates.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 4
Why this rank
Rank 2/10 after semantic revision; analyst score 9 = max(1, 4+3+2): topic overlap 4/4, complementarity 3/3, feasible first test 2/3. The experiment, numerical inputs or identity/scope needs confirmation before execution. An offline integration comparison can start with public data before a new experimental atlas or sequencing protocol; the experimental original remains a close scientific match. Original retained exactly at rank 2; preceding alternatives are Rahul Satija (10; 4+3+3). The preserved scientific explanation above describes the narrower contribution; current ordering follows these displayed component totals, not comparative researcher quality.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified.
Connection 3
Lior S. Pachter
California Institute of Technology
Proposed capability match: Tomer Kalisky's single-cell expression profiling, stem-cell biology can be paired with Lior S. Pachter's documented single-cell sequencing, RNA biology for longitudinal single-cell repair atlas. The specific contribution is RNA measurement and reproducible genomics computation; this transfer is an analyst hypothesis.[70][483]
First test and score details
First test
Compare two single-cell RNA quantification or representation pipelines on the same reads using a public longitudinal or staged tissue-repair single-cell dataset split by donor and time. Compare quantification disagreement, memory use and cell-state stability with a static cell-state classifier without trajectory information.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 3
Why this rank
Rank 3/10 after semantic revision; analyst score 9 = max(1, 3+3+3): topic overlap 3/4, complementarity 3/3, feasible first test 3/3. A bounded offline comparison is specified; required datasets and domain assumptions must still be checked.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified.
Show 7 moreShow fewer external connections
Connection 4
Karthik Shekhar
University of California, Berkeley
Proposed capability match: Tomer Kalisky's single-cell expression profiling, stem-cell biology can be paired with Karthik Shekhar's documented computational biology and genomics, neuroscience for longitudinal single-cell repair atlas. The specific contribution is genomic and neural population modelling; this transfer is an analyst hypothesis.[70][436]
First test and score details
First test
Compare cell-population representations using donor-held-out rather than random-cell splits using a public longitudinal or staged tissue-repair single-cell dataset split by donor and time. Compare population stability and held-out prediction error with a static cell-state classifier without trajectory information.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 3
Why this rank
Rank 4/10 after semantic revision; analyst score 9 = max(1, 3+3+3): topic overlap 3/4, complementarity 3/3, feasible first test 3/3. A bounded offline comparison is specified; required datasets and domain assumptions must still be checked.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified.
Connection 5
Michael Bronstein
University of Oxford
Proposed capability match: Tomer Kalisky's single-cell expression profiling, stem-cell biology can be paired with Michael Bronstein's documented geometric deep learning, graph neural networks for longitudinal single-cell repair atlas. The specific contribution is geometric structure and graph representations; this transfer is an analyst hypothesis.[70][74][442]
First test and score details
First test
Compare a geometry/graph-aware model with a parameter-matched unstructured baseline under structural perturbations using a public longitudinal or staged tissue-repair single-cell dataset split by donor and time. Compare held-out error, symmetry consistency and robustness to altered graph topology with a static cell-state classifier without trajectory information.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 2
Why this rank
Rank 5/10 after semantic revision; analyst score 8 = max(1, 2+3+3): topic overlap 2/4, complementarity 3/3, feasible first test 3/3. A bounded offline comparison is specified; required datasets and domain assumptions must still be checked.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified. The refreshed Oxford profile also lists an Aithyra scientific-director role; the original Oxford institution string is preserved.
Connection 6
Fei Chen
Broad Institute of MIT and Harvard
Proposed capability match for Tomer Kalisky with Fei Chen: Spatial tissue analysis is a close but conditional branch: a generic single-cell time course lacks coordinates, and the appropriate control changes spatial information while holding stage/count inputs fixed.[63][70][447]
First test and score details
First test
Audit for a repair time course with paired counts, spatial coordinates, donor and stage labels. Until confirmed, generate a synthetic staged tissue with planted cell neighborhoods. Compare spatial versus coordinate-free cell-state assignment on identical counts and time labels; computationally jitter coordinates and report neighborhood/state recovery against model truth.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 3
Why this rank
Rank 6/10 after semantic revision; analyst score 8 = max(1, 3+3+2): topic overlap 3/4, complementarity 3/3, feasible first test 2/3. Spatial tissue analysis is a close but conditional branch: a generic single-cell time course lacks coordinates, and the appropriate control changes spatial information while holding stage/count inputs fixed. The experiment, numerical inputs or identity/scope needs confirmation before execution.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified. Post-review scope: Spatial tissue analysis is a close but conditional branch: a generic single-cell time course lacks coordinates, and the appropriate control changes spatial information while holding stage/count inputs fixed. This revised proposal awaits independent targeted re-review; simulated outcomes would establish model behavior only, not biological, clinical or deployed benefit.
Connection 7
Yarin Gal
University of Oxford
Proposed capability match: Tomer Kalisky's single-cell expression profiling, stem-cell biology can be paired with Yarin Gal's documented Bayesian deep learning, uncertainty estimation for longitudinal single-cell repair atlas. The specific contribution is uncertainty and selective prediction; this transfer is an analyst hypothesis.[70][78][452]
First test and score details
First test
Compare uncertainty estimates with calibrated single-model and ensemble baselines under a predefined shift using a public longitudinal or staged tissue-repair single-cell dataset split by donor and time. Compare calibration error, risk-coverage and confident-error rate with a static cell-state classifier without trajectory information.
Score components
- complementarity
- 3
- feasible first test
- 3
- topic overlap
- 2
Why this rank
Rank 7/10 after semantic revision; analyst score 8 = max(1, 2+3+3): topic overlap 2/4, complementarity 3/3, feasible first test 3/3. A bounded offline comparison is specified; required datasets and domain assumptions must still be checked.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified.
Connection 8
Caroline Uhler
Massachusetts Institute of Technology
Proposed capability match for Tomer Kalisky with Caroline Uhler: Causal repair analysis needs a specified intervention and outcome; a time course alone does not supply intervention truth or establish causal transitions.[70][129][497]
First test and score details
First test
Define a synthetic repair-state transition model with a named intervention on one signalling variable and explicit confounders. Fit a transition predictor and a structural model to the same observational time courses; compare intervention-state predictions against held-out simulator truth. Report sensitivity to unmeasured confounding and stage misalignment.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 3
Why this rank
Rank 8/10 after semantic revision; analyst score 8 = max(1, 3+3+2): topic overlap 3/4, complementarity 3/3, feasible first test 2/3. Causal repair analysis needs a specified intervention and outcome; a time course alone does not supply intervention truth or establish causal transitions. A bounded offline comparison is specified; required datasets and domain assumptions must still be checked.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified. Post-review scope: Causal repair analysis needs a specified intervention and outcome; a time course alone does not supply intervention truth or establish causal transitions. This revised proposal awaits independent targeted re-review; simulated outcomes would establish model behavior only, not biological, clinical or deployed benefit.
Connection 9
Vadim Gladyshev
Harvard Medical School and Brigham and Women's Hospital
Proposed capability match for Tomer Kalisky with Vadim Gladyshev: Ageing expertise can examine confounding of repair signatures only when age metadata are present; tissue stage is not a substitute for donor age.[7][70][455]
First test and score details
First test
Require donor age, repair stage, cell counts and donor identifiers before an ageing analysis. Initially generate a synthetic count table with separate age and repair-stage effects; compare age-adjusted and unadjusted predictors of a fixed repair-state label using held-out donors and age strata. Report recovery of the planted repair effect and age-confounding sensitivity.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 9/10 after semantic revision; analyst score 7 = max(1, 2+3+2): topic overlap 2/4, complementarity 3/3, feasible first test 2/3. Ageing expertise can examine confounding of repair signatures only when age metadata are present; tissue stage is not a substitute for donor age. The experiment, numerical inputs or identity/scope needs confirmation before execution.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified. Post-review scope: Ageing expertise can examine confounding of repair signatures only when age metadata are present; tissue stage is not a substitute for donor age. This revised proposal awaits independent targeted re-review; simulated outcomes would establish model behavior only, not biological, clinical or deployed benefit.
Connection 10
Stephen Quake
Stanford University
Proposed capability match for Tomer Kalisky with Stephen Quake: Single-cell measurement expertise could diagnose sampling distortions in inferred repair trajectories; the first stage is computational and requires explicit capture assumptions.[70][487]
First test and score details
First test
Generate known cell-state proportions across synthetic repair stages and apply declared capture biases, doublets and dropout. Hold the downstream state classifier fixed; compare estimated trajectories with ideal-capture and biased-capture inputs using trajectory error and rare-state recovery. No physical dilution or isolation is performed on archived data.
Score components
- complementarity
- 3
- feasible first test
- 2
- topic overlap
- 2
Why this rank
Rank 10/10 after semantic revision; analyst score 7 = max(1, 2+3+2): topic overlap 2/4, complementarity 3/3, feasible first test 2/3. Single-cell measurement expertise could diagnose sampling distortions in inferred repair trajectories; the first stage is computational and requires explicit capture assumptions. The experiment, numerical inputs or identity/scope needs confirmation before execution.
Conditions
Proposed fit, not an assertion of a new or active relationship. Independent review pending; forecast confidence low. Partner interest, capacity, data access and any required experimental approvals/resources are unverified. Post-review scope: Single-cell measurement expertise could diagnose sampling distortions in inferred repair trajectories; the first stage is computational and requires explicit capture assumptions. This revised proposal awaits independent targeted re-review; simulated outcomes would establish model behavior only, not biological, clinical or deployed benefit.
Evidence & open questions
- No standalone current CV was verified.
Inspect claim ratings and independent review
Tomer Kalisky has source-grounded capabilities in single-cell genomics and tissue regeneration, represented here by single-cell expression profiling, stem-cell biology, cancer genomics. [70]
Moderate confidenceReview: reviewedThe sources establish public professional activity, not comparative quality, future performance, or willingness to participate.
Review record
- profiles_a: supports. Kalisky's BIU profile directly states single-cell genomics with applications to stem-cell biology, tissue regeneration and cancer, matching the bounded capability claim.
Hypothesis for 2027–2031: Tomer Kalisky could explore longitudinal single-cell repair atlas through the bounded first test described in this profile. [70][72]
Low confidenceReview: reviewedTrajectory inference is observational and may not identify causal repair mechanisms.
Review record
- profiles_a: supports. The proposed atlas is explicitly hypothetical and joins Kalisky's single-cell regeneration work with Teichmann's source-confirmed cell-atlas and tissue-architecture program. Observational trajectories remain non-causal.